From f339e1ce7d0eafeed3c42f2147f3d3bdecb9a00c Mon Sep 17 00:00:00 2001 From: FynnBe Date: Thu, 24 Oct 2024 14:32:22 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20bioimage?= =?UTF-8?q?-io/core-bioimage-io-python@646546f92d36fd75b4bd46fbc01ff6a6e39?= =?UTF-8?q?9707e=20=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- bioimageio/core/proc_ops.html | 2 +- bioimageio/core/sample.html | 4 ++-- bioimageio/core/stat_calculators.html | 30 +++++++++++++-------------- bioimageio/core/stat_measures.html | 10 ++++----- search.js | 2 +- 5 files changed, 24 insertions(+), 24 deletions(-) diff --git a/bioimageio/core/proc_ops.html b/bioimageio/core/proc_ops.html index 55072545..62f10d6a 100644 --- a/bioimageio/core/proc_ops.html +++ b/bioimageio/core/proc_ops.html @@ -1068,7 +1068,7 @@

- dataset_stats: Mapping[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]] + dataset_stats: Mapping[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]
diff --git a/bioimageio/core/sample.html b/bioimageio/core/sample.html index 82a063ab..501f5fb9 100644 --- a/bioimageio/core/sample.html +++ b/bioimageio/core/sample.html @@ -674,7 +674,7 @@

- stat: Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]] + stat: Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]
@@ -1373,7 +1373,7 @@
Inherited Members
- stat: Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]] + stat: Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]
diff --git a/bioimageio/core/stat_calculators.html b/bioimageio/core/stat_calculators.html index 2effda77..95e6feaa 100644 --- a/bioimageio/core/stat_calculators.html +++ b/bioimageio/core/stat_calculators.html @@ -926,7 +926,7 @@

def - compute( self, sample: bioimageio.core.sample.Sample) -> Dict[bioimageio.core.stat_measures.SampleMean, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]: + compute( self, sample: bioimageio.core.sample.Sample) -> Dict[bioimageio.core.stat_measures.SampleMean, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]: @@ -965,7 +965,7 @@

def - compute_and_update( self, sample: bioimageio.core.sample.Sample) -> Dict[bioimageio.core.stat_measures.SampleMean, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]: + compute_and_update( self, sample: bioimageio.core.sample.Sample) -> Dict[bioimageio.core.stat_measures.SampleMean, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]: @@ -986,7 +986,7 @@

def - finalize( self) -> Dict[bioimageio.core.stat_measures.DatasetMean, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]: + finalize( self) -> Dict[bioimageio.core.stat_measures.DatasetMean, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]: @@ -1129,7 +1129,7 @@

def - compute( self, sample: bioimageio.core.sample.Sample) -> Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleStd], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]: + compute( self, sample: bioimageio.core.sample.Sample) -> Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleStd], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]: @@ -1210,7 +1210,7 @@

def - finalize( self) -> Dict[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetStd], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]: + finalize( self) -> Dict[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetStd], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]: @@ -1314,7 +1314,7 @@

def - compute( self, sample: bioimageio.core.sample.Sample) -> Dict[bioimageio.core.stat_measures.SampleQuantile, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]: + compute( self, sample: bioimageio.core.sample.Sample) -> Dict[bioimageio.core.stat_measures.SampleQuantile, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]: @@ -1473,7 +1473,7 @@

def - finalize( self) -> Dict[bioimageio.core.stat_measures.DatasetPercentile, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]: + finalize( self) -> Dict[bioimageio.core.stat_measures.DatasetPercentile, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]: @@ -1657,7 +1657,7 @@

def - finalize( self) -> Dict[bioimageio.core.stat_measures.DatasetPercentile, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]: + finalize( self) -> Dict[bioimageio.core.stat_measures.DatasetPercentile, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]: @@ -1761,7 +1761,7 @@

def - compute( self, sample: bioimageio.core.sample.Sample) -> Dict[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]: + compute( self, sample: bioimageio.core.sample.Sample) -> Dict[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]: @@ -2010,7 +2010,7 @@

def - finalize( self) -> Dict[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]: + finalize( self) -> Dict[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]: @@ -2038,7 +2038,7 @@

def - update_and_get_all( self, sample: Union[bioimageio.core.sample.Sample, Iterable[bioimageio.core.sample.Sample]]) -> Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]: + update_and_get_all( self, sample: Union[bioimageio.core.sample.Sample, Iterable[bioimageio.core.sample.Sample]]) -> Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]: @@ -2067,7 +2067,7 @@

def - skip_update_and_get_all( self, sample: bioimageio.core.sample.Sample) -> Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]: + skip_update_and_get_all( self, sample: bioimageio.core.sample.Sample) -> Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]: @@ -2198,7 +2198,7 @@

def - compute_dataset_measures( measures: Iterable[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], dataset: Iterable[bioimageio.core.sample.Sample]) -> Dict[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]: + compute_dataset_measures( measures: Iterable[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], dataset: Iterable[bioimageio.core.sample.Sample]) -> Dict[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]: @@ -2234,7 +2234,7 @@

def - compute_sample_measures( measures: Iterable[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], sample: bioimageio.core.sample.Sample) -> Dict[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]: + compute_sample_measures( measures: Iterable[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], sample: bioimageio.core.sample.Sample) -> Dict[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]: @@ -2265,7 +2265,7 @@

def - compute_measures( measures: Iterable[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], dataset: Iterable[bioimageio.core.sample.Sample]) -> Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]: + compute_measures( measures: Iterable[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], dataset: Iterable[bioimageio.core.sample.Sample]) -> Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]: diff --git a/bioimageio/core/stat_measures.html b/bioimageio/core/stat_measures.html index c1c3a4e3..9af01677 100644 --- a/bioimageio/core/stat_measures.html +++ b/bioimageio/core/stat_measures.html @@ -852,7 +852,7 @@

@abstractmethod
def - compute( self, sample: SampleLike) -> Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]: + compute( self, sample: SampleLike) -> Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]: @@ -1071,7 +1071,7 @@

Inherited Members
def - compute( self, sample: SampleLike) -> Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]: + compute( self, sample: SampleLike) -> Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]: @@ -1317,7 +1317,7 @@
Inherited Members
def - compute( self, sample: SampleLike) -> Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]: + compute( self, sample: SampleLike) -> Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]: @@ -1563,7 +1563,7 @@
Inherited Members
def - compute( self, sample: SampleLike) -> Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]: + compute( self, sample: SampleLike) -> Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]: @@ -1810,7 +1810,7 @@
Inherited Members
def - compute( self, sample: SampleLike) -> Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]: + compute( self, sample: SampleLike) -> Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]: diff --git a/search.js b/search.js index 70828937..4db52c00 100644 --- a/search.js +++ b/search.js @@ -1,6 +1,6 @@ window.pdocSearch = (function(){ /** elasticlunr - http://weixsong.github.io * Copyright (C) 2017 Oliver Nightingale * Copyright (C) 2017 Wei Song * MIT Licensed */!function(){function e(e){if(null===e||"object"!=typeof e)return e;var t=e.constructor();for(var n in e)e.hasOwnProperty(n)&&(t[n]=e[n]);return t}var t=function(e){var n=new t.Index;return n.pipeline.add(t.trimmer,t.stopWordFilter,t.stemmer),e&&e.call(n,n),n};t.version="0.9.5",lunr=t,t.utils={},t.utils.warn=function(e){return function(t){e.console&&console.warn&&console.warn(t)}}(this),t.utils.toString=function(e){return void 0===e||null===e?"":e.toString()},t.EventEmitter=function(){this.events={}},t.EventEmitter.prototype.addListener=function(){var e=Array.prototype.slice.call(arguments),t=e.pop(),n=e;if("function"!=typeof t)throw new TypeError("last argument must be a function");n.forEach(function(e){this.hasHandler(e)||(this.events[e]=[]),this.events[e].push(t)},this)},t.EventEmitter.prototype.removeListener=function(e,t){if(this.hasHandler(e)){var n=this.events[e].indexOf(t);-1!==n&&(this.events[e].splice(n,1),0==this.events[e].length&&delete this.events[e])}},t.EventEmitter.prototype.emit=function(e){if(this.hasHandler(e)){var t=Array.prototype.slice.call(arguments,1);this.events[e].forEach(function(e){e.apply(void 0,t)},this)}},t.EventEmitter.prototype.hasHandler=function(e){return e in this.events},t.tokenizer=function(e){if(!arguments.length||null===e||void 0===e)return[];if(Array.isArray(e)){var n=e.filter(function(e){return null===e||void 0===e?!1:!0});n=n.map(function(e){return t.utils.toString(e).toLowerCase()});var i=[];return n.forEach(function(e){var n=e.split(t.tokenizer.seperator);i=i.concat(n)},this),i}return e.toString().trim().toLowerCase().split(t.tokenizer.seperator)},t.tokenizer.defaultSeperator=/[\s\-]+/,t.tokenizer.seperator=t.tokenizer.defaultSeperator,t.tokenizer.setSeperator=function(e){null!==e&&void 0!==e&&"object"==typeof e&&(t.tokenizer.seperator=e)},t.tokenizer.resetSeperator=function(){t.tokenizer.seperator=t.tokenizer.defaultSeperator},t.tokenizer.getSeperator=function(){return t.tokenizer.seperator},t.Pipeline=function(){this._queue=[]},t.Pipeline.registeredFunctions={},t.Pipeline.registerFunction=function(e,n){n in t.Pipeline.registeredFunctions&&t.utils.warn("Overwriting existing registered function: "+n),e.label=n,t.Pipeline.registeredFunctions[n]=e},t.Pipeline.getRegisteredFunction=function(e){return e in t.Pipeline.registeredFunctions!=!0?null:t.Pipeline.registeredFunctions[e]},t.Pipeline.warnIfFunctionNotRegistered=function(e){var n=e.label&&e.label in this.registeredFunctions;n||t.utils.warn("Function is not registered with pipeline. This may cause problems when serialising the index.\n",e)},t.Pipeline.load=function(e){var n=new t.Pipeline;return e.forEach(function(e){var i=t.Pipeline.getRegisteredFunction(e);if(!i)throw new Error("Cannot load un-registered function: "+e);n.add(i)}),n},t.Pipeline.prototype.add=function(){var e=Array.prototype.slice.call(arguments);e.forEach(function(e){t.Pipeline.warnIfFunctionNotRegistered(e),this._queue.push(e)},this)},t.Pipeline.prototype.after=function(e,n){t.Pipeline.warnIfFunctionNotRegistered(n);var i=this._queue.indexOf(e);if(-1===i)throw new Error("Cannot find existingFn");this._queue.splice(i+1,0,n)},t.Pipeline.prototype.before=function(e,n){t.Pipeline.warnIfFunctionNotRegistered(n);var i=this._queue.indexOf(e);if(-1===i)throw new Error("Cannot find existingFn");this._queue.splice(i,0,n)},t.Pipeline.prototype.remove=function(e){var t=this._queue.indexOf(e);-1!==t&&this._queue.splice(t,1)},t.Pipeline.prototype.run=function(e){for(var 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importing "+e.version);var n=new this;n._fields=e.fields,n._ref=e.ref,n.documentStore=t.DocumentStore.load(e.documentStore),n.pipeline=t.Pipeline.load(e.pipeline),n.index={};for(var i in e.index)n.index[i]=t.InvertedIndex.load(e.index[i]);return n},t.Index.prototype.addField=function(e){return this._fields.push(e),this.index[e]=new t.InvertedIndex,this},t.Index.prototype.setRef=function(e){return this._ref=e,this},t.Index.prototype.saveDocument=function(e){return this.documentStore=new t.DocumentStore(e),this},t.Index.prototype.addDoc=function(e,n){if(e){var n=void 0===n?!0:n,i=e[this._ref];this.documentStore.addDoc(i,e),this._fields.forEach(function(n){var o=this.pipeline.run(t.tokenizer(e[n]));this.documentStore.addFieldLength(i,n,o.length);var r={};o.forEach(function(e){e in r?r[e]+=1:r[e]=1},this);for(var s in r){var u=r[s];u=Math.sqrt(u),this.index[n].addToken(s,{ref:i,tf:u})}},this),n&&this.eventEmitter.emit("add",e,this)}},t.Index.prototype.removeDocByRef=function(e){if(e&&this.documentStore.isDocStored()!==!1&&this.documentStore.hasDoc(e)){var t=this.documentStore.getDoc(e);this.removeDoc(t,!1)}},t.Index.prototype.removeDoc=function(e,n){if(e){var n=void 0===n?!0:n,i=e[this._ref];this.documentStore.hasDoc(i)&&(this.documentStore.removeDoc(i),this._fields.forEach(function(n){var o=this.pipeline.run(t.tokenizer(e[n]));o.forEach(function(e){this.index[n].removeToken(e,i)},this)},this),n&&this.eventEmitter.emit("remove",e,this))}},t.Index.prototype.updateDoc=function(e,t){var t=void 0===t?!0:t;this.removeDocByRef(e[this._ref],!1),this.addDoc(e,!1),t&&this.eventEmitter.emit("update",e,this)},t.Index.prototype.idf=function(e,t){var n="@"+t+"/"+e;if(Object.prototype.hasOwnProperty.call(this._idfCache,n))return this._idfCache[n];var i=this.index[t].getDocFreq(e),o=1+Math.log(this.documentStore.length/(i+1));return this._idfCache[n]=o,o},t.Index.prototype.getFields=function(){return this._fields.slice()},t.Index.prototype.search=function(e,n){if(!e)return[];e="string"==typeof e?{any:e}:JSON.parse(JSON.stringify(e));var i=null;null!=n&&(i=JSON.stringify(n));for(var o=new t.Configuration(i,this.getFields()).get(),r={},s=Object.keys(e),u=0;u0&&t.push(e);for(var i in n)"docs"!==i&&"df"!==i&&this.expandToken(e+i,t,n[i]);return t},t.InvertedIndex.prototype.toJSON=function(){return{root:this.root}},t.Configuration=function(e,n){var e=e||"";if(void 0==n||null==n)throw new Error("fields should not be null");this.config={};var i;try{i=JSON.parse(e),this.buildUserConfig(i,n)}catch(o){t.utils.warn("user configuration parse failed, will use default configuration"),this.buildDefaultConfig(n)}},t.Configuration.prototype.buildDefaultConfig=function(e){this.reset(),e.forEach(function(e){this.config[e]={boost:1,bool:"OR",expand:!1}},this)},t.Configuration.prototype.buildUserConfig=function(e,n){var i="OR",o=!1;if(this.reset(),"bool"in e&&(i=e.bool||i),"expand"in e&&(o=e.expand||o),"fields"in e)for(var r in e.fields)if(n.indexOf(r)>-1){var s=e.fields[r],u=o;void 0!=s.expand&&(u=s.expand),this.config[r]={boost:s.boost||0===s.boost?s.boost:1,bool:s.bool||i,expand:u}}else t.utils.warn("field name in user configuration not found in index instance fields");else this.addAllFields2UserConfig(i,o,n)},t.Configuration.prototype.addAllFields2UserConfig=function(e,t,n){n.forEach(function(n){this.config[n]={boost:1,bool:e,expand:t}},this)},t.Configuration.prototype.get=function(){return this.config},t.Configuration.prototype.reset=function(){this.config={}},lunr.SortedSet=function(){this.length=0,this.elements=[]},lunr.SortedSet.load=function(e){var t=new this;return t.elements=e,t.length=e.length,t},lunr.SortedSet.prototype.add=function(){var e,t;for(e=0;e1;){if(r===e)return o;e>r&&(t=o),r>e&&(n=o),i=n-t,o=t+Math.floor(i/2),r=this.elements[o]}return r===e?o:-1},lunr.SortedSet.prototype.locationFor=function(e){for(var t=0,n=this.elements.length,i=n-t,o=t+Math.floor(i/2),r=this.elements[o];i>1;)e>r&&(t=o),r>e&&(n=o),i=n-t,o=t+Math.floor(i/2),r=this.elements[o];return r>e?o:e>r?o+1:void 0},lunr.SortedSet.prototype.intersect=function(e){for(var t=new lunr.SortedSet,n=0,i=0,o=this.length,r=e.length,s=this.elements,u=e.elements;;){if(n>o-1||i>r-1)break;s[n]!==u[i]?s[n]u[i]&&i++:(t.add(s[n]),n++,i++)}return t},lunr.SortedSet.prototype.clone=function(){var e=new lunr.SortedSet;return e.elements=this.toArray(),e.length=e.elements.length,e},lunr.SortedSet.prototype.union=function(e){var t,n,i;this.length>=e.length?(t=this,n=e):(t=e,n=this),i=t.clone();for(var o=0,r=n.toArray();o\"License\"\n\"PyPI\"\n\"conda-version\"\n\"downloads\"\n\"conda-forge\n\"code

\n\n

core-bioimage-io-python

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Python specific core utilities for bioimage.io resources (in particular models).

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Get started

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To get started we recommend installing bioimageio.core with conda together with a deep\nlearning framework, e.g. pytorch, and run a few bioimageio commands to see what\nbioimage.core has to offer:

\n\n
    \n

  1. install with conda (for more details on conda environments, checkout the conda docs)

    \n\n
    \n
    conda install -c conda-forge bioimageio.core pytorch\n
    \n
    2. \n\n

  2. test a model

    \n\n
    \n
    $ bioimageio test powerful-chipmunk\n...\n
    \n
    \n\n

    \n(Click to expand output)

    \n\n
    \n
      \u2714\ufe0f                 bioimageio validation passed\n\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\n  source            https://uk1s3.embassy.ebi.ac.uk/public-datasets/bioimage.io/powerful-chipmunk/1/files/rdf.yaml\n  format version    model 0.4.10\n  bioimageio.spec   0.5.3post4\n  bioimageio.core   0.6.8\n\n\n\n  \u2753   location                                     detail\n\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\n  \u2714\ufe0f                                                 initialized ModelDescr to describe model 0.4.10\n\n  \u2714\ufe0f                                                 bioimageio.spec format validation model 0.4.10\n  \ud83d\udd0d   context.perform_io_checks                    True\n  \ud83d\udd0d   context.root                                 https://uk1s3.embassy.ebi.ac.uk/public-datasets/bioimage.io/powerful-chipmunk/1/files\n  \ud83d\udd0d   context.known_files.weights.pt               3bd9c518c8473f1e35abb7624f82f3aa92f1015e66fb1f6a9d08444e1f2f5698\n  \ud83d\udd0d   context.known_files.weights-torchscript.pt   4e568fd81c0ffa06ce13061327c3f673e1bac808891135badd3b0fcdacee086b\n  \ud83d\udd0d   context.warning_level                        error\n\n  \u2714\ufe0f                                                 Reproduce test outputs from test inputs\n\n  \u2714\ufe0f                                                 Reproduce test outputs from test inputs\n
    \n
    \n\n

    \n\n

    or

    \n\n
    \n
    $ bioimageio test impartial-shrimp\n...\n
    \n
    \n\n

    (Click to expand output)

    \n\n
    \n
      \u2714\ufe0f                 bioimageio validation passed\n\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\n  source            https://uk1s3.embassy.ebi.ac.uk/public-datasets/bioimage.io/impartial-shrimp/1.1/files/rdf.yaml\n  format version    model 0.5.3\n  bioimageio.spec   0.5.3.2\n  bioimageio.core   0.6.9\n\n\n  \u2753   location                    detail\n\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\n  \u2714\ufe0f                                initialized ModelDescr to describe model 0.5.3\n\n\n  \u2714\ufe0f                                bioimageio.spec format validation model 0.5.3\n\n  \ud83d\udd0d   context.perform_io_checks   False\n  \ud83d\udd0d   context.warning_level       error\n\n  \u2714\ufe0f                                Reproduce test outputs from test inputs (pytorch_state_dict)\n\n\n  \u2714\ufe0f                                Run pytorch_state_dict inference for inputs with batch_size: 1 and size parameter n:\n\n                                  0\n\n  \u2714\ufe0f                                Run pytorch_state_dict inference for inputs with batch_size: 2 and size parameter n:\n\n                                  0\n\n  \u2714\ufe0f                                Run pytorch_state_dict inference for inputs with batch_size: 1 and size parameter n:\n\n                                  1\n\n  \u2714\ufe0f                                Run pytorch_state_dict inference for inputs with batch_size: 2 and size parameter n:\n\n                                  1\n\n  \u2714\ufe0f                                Run pytorch_state_dict inference for inputs with batch_size: 1 and size parameter n:\n\n                                  2\n\n  \u2714\ufe0f                                Run pytorch_state_dict inference for inputs with batch_size: 2 and size parameter n:\n\n                                  2\n\n  \u2714\ufe0f                                Reproduce test outputs from test inputs (torchscript)\n\n\n  \u2714\ufe0f                                Run torchscript inference for inputs with batch_size: 1 and size parameter n: 0\n\n\n  \u2714\ufe0f                                Run torchscript inference for inputs with batch_size: 2 and size parameter n: 0\n\n\n  \u2714\ufe0f                                Run torchscript inference for inputs with batch_size: 1 and size parameter n: 1\n\n\n  \u2714\ufe0f                                Run torchscript inference for inputs with batch_size: 2 and size parameter n: 1\n\n\n  \u2714\ufe0f                                Run torchscript inference for inputs with batch_size: 1 and size parameter n: 2\n\n\n  \u2714\ufe0f                                Run torchscript inference for inputs with batch_size: 2 and size parameter n: 2\n
    \n
    \n\n

    3. \n
  3. run prediction on your data
    4. \n
\n\n
    \n

  • display the bioimageio-predict command help to get an overview:

    \n\n
    \n
    $ bioimageio predict --help\n...\n
    \n
    \n\n

    \n(Click to expand output)

    \n\n
    \n
    usage: bioimageio predict [-h] [--inputs Sequence[Union[str,Annotated[Tuple[str,...],MinLenmin_length=1]]]]\n                          [--outputs {str,Tuple[str,...]}] [--overwrite bool] [--blockwise bool] [--stats Path]\n                          [--preview bool]\n                          [--weight_format {typing.Literal['keras_hdf5','onnx','pytorch_state_dict','tensorflow_js','tensorflow_saved_model_bundle','torchscript'],any}]\n                          [--example bool]\n                          SOURCE\n\nbioimageio-predict - Run inference on your data with a bioimage.io model.\n\npositional arguments:\n  SOURCE                Url/path to a bioimageio.yaml/rdf.yaml file\n                        or a bioimage.io resource identifier, e.g. 'affable-shark'\n\noptional arguments:\n  -h, --help            show this help message and exit\n  --inputs Sequence[Union[str,Annotated[Tuple[str,...],MinLen(min_length=1)]]]\n                        Model input sample paths (for each input tensor)\n\n                        The input paths are expected to have shape...\n                        - (n_samples,) or (n_samples,1) for models expecting a single input tensor\n                        - (n_samples,) containing the substring '{input_id}', or\n                        - (n_samples, n_model_inputs) to provide each input tensor path explicitly.\n\n                        All substrings that are replaced by metadata from the model description:\n                        - '{model_id}'\n                        - '{input_id}'\n\n                        Example inputs to process sample 'a' and 'b'\n                        for a model expecting a 'raw' and a 'mask' input tensor:\n                        --inputs="[["a_raw.tif","a_mask.tif"],["b_raw.tif","b_mask.tif"]]"\n                        (Note that JSON double quotes need to be escaped.)\n\n                        Alternatively a `bioimageio-cli.yaml` (or `bioimageio-cli.json`) file\n                        may provide the arguments, e.g.:\n                        ```yaml\n                        inputs:\n                        - [a_raw.tif, a_mask.tif]\n                        - [b_raw.tif, b_mask.tif]\n                   \n
    \n
    \n\n
                        `.npy` and any file extension supported by imageio are supported.\n                    Aavailable formats are listed at\n                    https://imageio.readthedocs.io/en/stable/formats/index.html#all-formats.\n                    Some formats have additional dependencies.\n\n                    \u200a (default: ('{input_id}/001.tif',))\n
    \n\n

    --outputs {str,Tuple[str,...]}\n Model output path pattern (per output tensor)

    \n\n
                        All substrings that are replaced:\n                    - '{model_id}' (from model description)\n                    - '{output_id}' (from model description)\n                    - '{sample_id}' (extracted from input paths)\n\n                    \u200a (default: outputs_{model_id}/{output_id}/{sample_id}.tif)\n
    \n\n

    --overwrite bool allow overwriting existing output files (default: False)\n --blockwise bool process inputs blockwise (default: False)\n --stats Path path to dataset statistics\n (will be written if it does not exist,\n but the model requires statistical dataset measures)\n \u200a (default: dataset_statistics.json)\n --preview bool preview which files would be processed\n and what outputs would be generated. (default: False)\n --weight_format {typing.Literal['keras_hdf5','onnx','pytorch_state_dict','tensorflow_js','tensorflow_saved_model_bundle','torchscript'],any}\n The weight format to use. (default: any)\n --example bool generate and run an example

    \n\n
                        1. downloads example model inputs\n                    2. creates a `{model_id}_example` folder\n                    3. writes input arguments to `{model_id}_example/bioimageio-cli.yaml`\n                    4. executes a preview dry-run\n                    5. executes prediction with example input\n\n                    \u200a (default: False)\n
    • \n
\n\n
\n    </details>\n\n- create an example and run prediction locally!\n\n    ```console\n    $ bioimageio predict impartial-shrimp --example=True\n    ...\n
\n\n
<details>\n<summary>(Click to expand output)</summary>\n\n```console\n\ud83d\udec8 bioimageio prediction preview structure:\n{'{sample_id}': {'inputs': {'{input_id}': '<input path>'},\n                'outputs': {'{output_id}': '<output path>'}}}\n\ud83d\udd0e bioimageio prediction preview output:\n{'1': {'inputs': {'input0': 'impartial-shrimp_example/input0/001.tif'},\n      'outputs': {'output0': 'impartial-shrimp_example/outputs/output0/1.tif'}}}\npredict with impartial-shrimp: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 1/1 [00:21<00:00, 21.76s/sample]\n\ud83c\udf89 Sucessfully ran example prediction!\nTo predict the example input using the CLI example config file impartial-shrimp_example\\bioimageio-cli.yaml, execute `bioimageio predict` from impartial-shrimp_example:\n$ cd impartial-shrimp_example\n$ bioimageio predict \"impartial-shrimp\"\n\nAlternatively run the following command in the current workind directory, not the example folder:\n$ bioimageio predict --preview=False --overwrite=True --stats=\"impartial-shrimp_example/dataset_statistics.json\" --inputs=\"[[\\\"impartial-shrimp_example/input0/001.tif\\\"]]\" --outputs=\"impartial-shrimp_example/outputs/{output_id}/{sample_id}.tif\" \"impartial-shrimp\"\n(note that a local 'bioimageio-cli.json' or 'bioimageio-cli.yaml' may interfere with this)\n
\n\n
\n  </details>\n\n## Installation\n\n### Via Mamba/Conda\n\nThe `bioimageio.core` package can be installed from conda-forge via\n\n```console\nmamba install -c conda-forge bioimageio.core\n```\n\nIf you do not install any additional deep learning libraries, you will only be able to use general convenience\nfunctionality, but not any functionality for model prediction.\nTo install additional deep learning libraries use:\n\n- Pytorch/Torchscript:\n\n  CPU installation (if you don't have an nvidia graphics card):\n\n  ```console\n  mamba install -c pytorch -c conda-forge bioimageio.core pytorch torchvision cpuonly\n
\n\n

GPU installation (for cuda 11.6, please choose the appropriate cuda version for your system):

\n\n

\n
mamba install -c pytorch -c nvidia -c conda-forge bioimageio.core pytorch torchvision pytorch-cuda=11.8\n
\n

\n\n

Note that the pytorch installation instructions may change in the future. For the latest instructions please refer to pytorch.org.

\n\n
    \n

  • Tensorflow

    \n\n

    Currently only CPU version supported

    \n\n
    \n
    mamba install -c conda-forge bioimageio.core tensorflow\n
    \n
    • \n\n

  • ONNXRuntime

    \n\n

    Currently only cpu version supported

    \n\n
    \n
    mamba install -c conda-forge bioimageio.core onnxruntime\n
    \n
    • \n
\n\n

Via pip

\n\n

The package is also available via pip\n(e.g. with recommended extras onnx and pytorch):

\n\n
\n
pip install "bioimageio.core[onnx,pytorch]"\n
\n
\n\n

Set up Development Environment

\n\n

To set up a development conda environment run the following commands:

\n\n
\n
mamba env create -f dev/env.yaml\nmamba activate core\npip install -e . --no-deps\n
\n
\n\n

There are different environment files available that only install tensorflow or pytorch as dependencies.

\n\n

\ud83d\udcbb Use the Command Line Interface

\n\n

bioimageio.core installs a command line interface (CLI) for testing models and other functionality.\nYou can list all the available commands via:

\n\n
\n
bioimageio\n
\n
\n\n

CLI inputs from file

\n\n

For convenience the command line options (not arguments) may be given in a bioimageio-cli.json\nor bioimageio-cli.yaml file, e.g.:

\n\n
\n
# bioimageio-cli.yaml\ninputs: inputs/*_{tensor_id}.h5\noutputs: outputs_{model_id}/{sample_id}_{tensor_id}.h5\noverwrite: true\nblockwise: true\nstats: inputs/dataset_statistics.json\n
\n
\n\n

\ud83d\udc0d Use in Python

\n\n

bioimageio.core is a python package that implements prediction with bioimageio models\nincluding standardized pre- and postprocessing operations.\nThese models are described by---and can be loaded with---the bioimageio.spec package.

\n\n

In addition bioimageio.core provides functionality to convert model weight formats.

\n\n

To get an overview of this functionality, check out these example notebooks:

\n\n\n\n

and the developer documentation.

\n\n

Logging level

\n\n

bioimageio.spec and bioimageio.core use loguru for logging, hence the logging level\nmay be controlled with the LOGURU_LEVEL environment variable.

\n\n

Model Specification

\n\n

The model specification and its validation tools can be found at https://github.com/bioimage-io/spec-bioimage-io.

\n\n

Changelog

\n\n

0.6.9

\n\n
    \n
  • improve bioimageio command line interface (details in #157)\n
      \n
    • add predict command
      • \n
    • package command input path is now required
      • \n
    • \n
\n\n

0.6.8

\n\n
    \n
  • testing model inference will now check all weight formats\n(previously only the first one for which model adapter creation succeeded had been checked)
    • \n
  • fix predict with blocking (Thanks @thodkatz)
    • \n
\n\n

0.6.7

\n\n
    \n
  • predict() argument inputs may be sample
    • \n
\n\n

0.6.6

\n\n
    \n
  • add aliases to match previous API more closely
    • \n
\n\n

0.6.5

\n\n
    \n
  • improve adapter error messages
    • \n
\n\n

0.6.4

\n\n
    \n
  • add bioimageio validate-format command
    • \n
  • improve error messages and display of command results
    • \n
\n\n

0.6.3

\n\n
    \n
  • Fix #386
    • \n
  • (in model inference testing) stop assuming model inputs are tileable
    • \n
\n\n

0.6.2

\n\n\n\n

0.6.1

\n\n\n\n

0.6.0

\n\n
    \n
  • add compatibility with new bioimageio.spec 0.5 (0.5.2post1)
    • \n
  • improve interfaces
    • \n
\n\n

0.5.10

\n\n\n"}, "bioimageio.core.test_resource": {"fullname": "bioimageio.core.test_resource", "modulename": "bioimageio.core", "qualname": "test_resource", "kind": "function", "doc": "

Test a bioimage.io resource dynamically, e.g. prediction of test tensors for models

\n", "signature": "(\tsource: Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], Dict[str, YamlValue]],\t*,\tformat_version: Union[Literal['discover', 'latest'], str] = 'discover',\tweight_format: Optional[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']] = None,\tdevices: Optional[Sequence[str]] = None,\tabsolute_tolerance: float = 0.00015,\trelative_tolerance: float = 0.0001,\tdecimal: Optional[int] = None,\texpected_type: Optional[str] = None) -> bioimageio.spec.summary.ValidationSummary:", "funcdef": "def"}, "bioimageio.core.load_resource": {"fullname": "bioimageio.core.load_resource", "modulename": "bioimageio.core", "qualname": "load_resource", "kind": "function", "doc": "

load a bioimage.io resource description

\n\n

Args:\n source: Path or URL to an rdf.yaml or a bioimage.io package\n (zip-file with rdf.yaml in it).\n format_version: (optional) Use this argument to load the resource and\n convert its metadata to a higher format_version.\n perform_io_checks: Wether or not to perform validation that requires file io,\n e.g. downloading a remote files. The existence of local\n absolute file paths is still being checked.\n known_files: Allows to bypass download and hashing of referenced files\n (even if perform_io_checks is True).

\n\n

Returns:\n An object holding all metadata of the bioimage.io resource

\n", "signature": "(\tsource: Union[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]],\t/,\t*,\tformat_version: Union[Literal['discover'], Literal['latest'], str] = 'discover',\tperform_io_checks: bool = True,\tknown_files: Optional[Dict[str, bioimageio.spec._internal.io_basics.Sha256]] = None) -> Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.spec._internal.common_nodes.InvalidDescr]:", "funcdef": "def"}, "bioimageio.core.load_model": {"fullname": "bioimageio.core.load_model", "modulename": "bioimageio.core", "qualname": "load_model", "kind": "function", "doc": "

same as load_description, but addtionally ensures that the loaded\ndescription is valid and of type 'model'.

\n", "signature": "(\tsource: Union[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]],\t/,\t*,\tformat_version: Union[Literal['discover'], Literal['latest'], str] = 'discover',\tperform_io_checks: bool = True,\tknown_files: Optional[Dict[str, bioimageio.spec._internal.io_basics.Sha256]] = None) -> Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]:", "funcdef": "def"}, "bioimageio.core.axis": {"fullname": "bioimageio.core.axis", "modulename": "bioimageio.core.axis", "kind": "module", "doc": "

\n"}, "bioimageio.core.axis.AxisId": {"fullname": "bioimageio.core.axis.AxisId", "modulename": "bioimageio.core.axis", "qualname": "AxisId", "kind": "class", "doc": "

str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str

\n\n

Create a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to sys.getdefaultencoding().\nerrors defaults to 'strict'.

\n", "bases": "bioimageio.spec._internal.types.LowerCaseIdentifier"}, "bioimageio.core.axis.AxisId.root_model": {"fullname": "bioimageio.core.axis.AxisId.root_model", "modulename": "bioimageio.core.axis", "qualname": "AxisId.root_model", "kind": "variable", "doc": "

the pydantic root model to validate the string

\n", "annotation": ": ClassVar[Type[pydantic.root_model.RootModel[Any]]]", "default_value": "<class 'pydantic.root_model.RootModel[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]'>"}, "bioimageio.core.axis.PerAxis": {"fullname": "bioimageio.core.axis.PerAxis", "modulename": "bioimageio.core.axis", "qualname": "PerAxis", "kind": "variable", "doc": "

\n", "default_value": "typing.Mapping[bioimageio.spec.model.v0_5.AxisId, ~T]"}, "bioimageio.core.axis.BatchSize": {"fullname": "bioimageio.core.axis.BatchSize", "modulename": "bioimageio.core.axis", "qualname": "BatchSize", "kind": "variable", "doc": "

\n", "default_value": "<class 'int'>"}, "bioimageio.core.axis.AxisLetter": {"fullname": "bioimageio.core.axis.AxisLetter", "modulename": "bioimageio.core.axis", "qualname": "AxisLetter", "kind": "variable", "doc": "

\n", "default_value": "typing.Literal['b', 'i', 't', 'c', 'z', 'y', 'x']"}, "bioimageio.core.axis.AxisLike": {"fullname": "bioimageio.core.axis.AxisLike", "modulename": "bioimageio.core.axis", "qualname": "AxisLike", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bioimageio.spec.model.v0_5.AxisId, typing.Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, typing.Annotated[typing.Union[typing.Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], typing.Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[typing.Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], typing.Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], ForwardRef('Axis')]"}, "bioimageio.core.axis.Axis": {"fullname": "bioimageio.core.axis.Axis", "modulename": "bioimageio.core.axis", "qualname": "Axis", "kind": "class", "doc": "

\n"}, "bioimageio.core.axis.Axis.__init__": {"fullname": "bioimageio.core.axis.Axis.__init__", "modulename": "bioimageio.core.axis", "qualname": "Axis.__init__", "kind": "function", "doc": "

\n", "signature": "(\tid: bioimageio.spec.model.v0_5.AxisId,\ttype: Literal['batch', 'channel', 'index', 'space', 'time'])"}, "bioimageio.core.axis.Axis.id": {"fullname": "bioimageio.core.axis.Axis.id", "modulename": "bioimageio.core.axis", "qualname": "Axis.id", "kind": "variable", "doc": "

\n", "annotation": ": bioimageio.spec.model.v0_5.AxisId"}, "bioimageio.core.axis.Axis.type": {"fullname": "bioimageio.core.axis.Axis.type", "modulename": "bioimageio.core.axis", "qualname": "Axis.type", "kind": "variable", "doc": "

\n", "annotation": ": Literal['batch', 'channel', 'index', 'space', 'time']"}, "bioimageio.core.axis.Axis.create": {"fullname": "bioimageio.core.axis.Axis.create", "modulename": "bioimageio.core.axis", "qualname": "Axis.create", "kind": "function", "doc": "

\n", "signature": "(\tcls,\taxis: Union[bioimageio.spec.model.v0_5.AxisId, Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis]) -> bioimageio.core.axis.Axis:", "funcdef": "def"}, "bioimageio.core.axis.AxisInfo": {"fullname": "bioimageio.core.axis.AxisInfo", "modulename": "bioimageio.core.axis", "qualname": "AxisInfo", "kind": "class", "doc": "

\n", "bases": "Axis"}, "bioimageio.core.axis.AxisInfo.__init__": {"fullname": "bioimageio.core.axis.AxisInfo.__init__", "modulename": "bioimageio.core.axis", "qualname": "AxisInfo.__init__", "kind": "function", "doc": "

\n", "signature": "(\tid: bioimageio.spec.model.v0_5.AxisId,\ttype: Literal['batch', 'channel', 'index', 'space', 'time'],\tmaybe_singleton: bool)"}, "bioimageio.core.axis.AxisInfo.maybe_singleton": {"fullname": "bioimageio.core.axis.AxisInfo.maybe_singleton", "modulename": "bioimageio.core.axis", "qualname": "AxisInfo.maybe_singleton", "kind": "variable", "doc": "

\n", "annotation": ": bool"}, "bioimageio.core.axis.AxisInfo.create": {"fullname": "bioimageio.core.axis.AxisInfo.create", "modulename": "bioimageio.core.axis", "qualname": "AxisInfo.create", "kind": "function", "doc": "

\n", "signature": "(\tcls,\taxis: Union[bioimageio.spec.model.v0_5.AxisId, Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis],\tmaybe_singleton: Optional[bool] = None) -> bioimageio.core.axis.AxisInfo:", "funcdef": "def"}, "bioimageio.core.block": {"fullname": "bioimageio.core.block", "modulename": "bioimageio.core.block", "kind": "module", "doc": "

\n"}, "bioimageio.core.block.Block": {"fullname": "bioimageio.core.block.Block", "modulename": "bioimageio.core.block", "qualname": "Block", "kind": "class", "doc": "

A block/tile of a (larger) tensor

\n", "bases": "bioimageio.core.block_meta.BlockMeta"}, "bioimageio.core.block.Block.__init__": {"fullname": "bioimageio.core.block.Block.__init__", "modulename": "bioimageio.core.block", "qualname": "Block.__init__", "kind": "function", "doc": "

\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\tinner_slice: Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.SliceInfo],\thalo: Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.Halo],\tblock_index: int,\tblocks_in_sample: int,\tdata: bioimageio.core.tensor.Tensor)"}, "bioimageio.core.block.Block.data": {"fullname": "bioimageio.core.block.Block.data", "modulename": "bioimageio.core.block", "qualname": "Block.data", "kind": "variable", "doc": "

the block's tensor, e.g. a (padded) slice of some larger, original tensor

\n", "annotation": ": bioimageio.core.tensor.Tensor"}, "bioimageio.core.block.Block.inner_data": {"fullname": "bioimageio.core.block.Block.inner_data", "modulename": "bioimageio.core.block", "qualname": "Block.inner_data", "kind": "variable", "doc": "

\n"}, "bioimageio.core.block.Block.from_sample_member": {"fullname": "bioimageio.core.block.Block.from_sample_member", "modulename": "bioimageio.core.block", "qualname": "Block.from_sample_member", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tsample_member: bioimageio.core.tensor.Tensor,\tblock: bioimageio.core.block_meta.BlockMeta,\t*,\tpad_mode: Literal['edge', 'reflect', 'symmetric']) -> Self:", "funcdef": "def"}, "bioimageio.core.block.Block.get_transformed": {"fullname": "bioimageio.core.block.Block.get_transformed", "modulename": "bioimageio.core.block", "qualname": "Block.get_transformed", "kind": "function", "doc": "

\n", "signature": "(\tself,\tnew_axes: Mapping[bioimageio.spec.model.v0_5.AxisId, Union[bioimageio.core.block_meta.LinearAxisTransform, int]]) -> Self:", "funcdef": "def"}, "bioimageio.core.block.Block.from_meta": {"fullname": "bioimageio.core.block.Block.from_meta", "modulename": "bioimageio.core.block", "qualname": "Block.from_meta", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tmeta: bioimageio.core.block_meta.BlockMeta,\tdata: bioimageio.core.tensor.Tensor) -> Self:", "funcdef": "def"}, "bioimageio.core.block.split_tensor_into_blocks": {"fullname": "bioimageio.core.block.split_tensor_into_blocks", "modulename": "bioimageio.core.block", "qualname": "split_tensor_into_blocks", "kind": "function", "doc": "

divide a sample tensor into tensor blocks.

\n", "signature": "(\ttensor: bioimageio.core.tensor.Tensor,\tblock_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\t*,\thalo: Mapping[bioimageio.spec.model.v0_5.AxisId, Union[int, Tuple[int, int], bioimageio.core.common.Halo]],\tstride: Optional[Mapping[bioimageio.spec.model.v0_5.AxisId, int]] = None,\tpad_mode: Literal['edge', 'reflect', 'symmetric']) -> Tuple[int, Generator[bioimageio.core.block.Block, Any, NoneType]]:", "funcdef": "def"}, "bioimageio.core.block_meta": {"fullname": "bioimageio.core.block_meta", "modulename": "bioimageio.core.block_meta", "kind": "module", "doc": "

\n"}, "bioimageio.core.block_meta.LinearAxisTransform": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform", "kind": "class", "doc": "

\n"}, "bioimageio.core.block_meta.LinearAxisTransform.__init__": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform.__init__", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform.__init__", "kind": "function", "doc": "

\n", "signature": "(axis: bioimageio.spec.model.v0_5.AxisId, scale: float, offset: int)"}, "bioimageio.core.block_meta.LinearAxisTransform.axis": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform.axis", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform.axis", "kind": "variable", "doc": "

\n", "annotation": ": bioimageio.spec.model.v0_5.AxisId"}, "bioimageio.core.block_meta.LinearAxisTransform.scale": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform.scale", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform.scale", "kind": "variable", "doc": "

\n", "annotation": ": float"}, "bioimageio.core.block_meta.LinearAxisTransform.offset": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform.offset", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform.offset", "kind": "variable", "doc": "

\n", "annotation": ": int"}, "bioimageio.core.block_meta.LinearAxisTransform.compute": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform.compute", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform.compute", "kind": "function", "doc": "

\n", "signature": "(\tself,\ts: int,\tround: Callable[[float], int] = <built-in function floor>) -> int:", "funcdef": "def"}, "bioimageio.core.block_meta.BlockMeta": {"fullname": "bioimageio.core.block_meta.BlockMeta", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta", "kind": "class", "doc": "

Block meta data of a sample member (a tensor in a sample)

\n\n

Figure for illustration:\nThe first 2d block (dashed) of a sample member (bold).\nThe inner slice (thin) is expanded by a halo in both dimensions on both sides.\nThe outer slice reaches from the sample member origin (0, 0) to the right halo point.

\n\n
\u250c \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500  \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2510\n\u2577 halo(left)                         \u2577\n\u2577                                    \u2577\n\u2577  (0, 0)\u250f\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u252f\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u252f\u2501\u2501\u2501\u2794\n\u2577        \u2503                 \u2502         \u2577  sample member\n\u2577        \u2503      inner      \u2502         \u2577\n\u2577        \u2503   (and outer)   \u2502  outer  \u2577\n\u2577        \u2503      slice      \u2502  slice  \u2577\n\u2577        \u2503                 \u2502         \u2577\n\u2577        \u2523\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518         \u2577\n\u2577        \u2503   outer slice             \u2577\n\u2577        \u2503               halo(right) \u2577\n\u2514 \u2500 \u2500 \u2500 \u2500\u2503\u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500\u2518\n         \u2b07\n
\n\n

note:

\n\n
    \n
  • Inner and outer slices are specified in sample member coordinates.
    • \n
  • The outer_slice of a block at the sample edge may overlap by more than the\nhalo with the neighboring block (the inner slices will not overlap though).
    • \n
\n"}, "bioimageio.core.block_meta.BlockMeta.__init__": {"fullname": "bioimageio.core.block_meta.BlockMeta.__init__", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.__init__", "kind": "function", "doc": "

\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\tinner_slice: Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.SliceInfo],\thalo: Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.Halo],\tblock_index: int,\tblocks_in_sample: int)"}, "bioimageio.core.block_meta.BlockMeta.sample_shape": {"fullname": "bioimageio.core.block_meta.BlockMeta.sample_shape", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.sample_shape", "kind": "variable", "doc": "

the axis sizes of the whole (unblocked) sample

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, int]"}, "bioimageio.core.block_meta.BlockMeta.inner_slice": {"fullname": "bioimageio.core.block_meta.BlockMeta.inner_slice", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.inner_slice", "kind": "variable", "doc": "

inner region (without halo) wrt the sample

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.SliceInfo]"}, "bioimageio.core.block_meta.BlockMeta.halo": {"fullname": "bioimageio.core.block_meta.BlockMeta.halo", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.halo", "kind": "variable", "doc": "

halo enlarging the inner region to the block's sizes

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.Halo]"}, "bioimageio.core.block_meta.BlockMeta.block_index": {"fullname": "bioimageio.core.block_meta.BlockMeta.block_index", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.block_index", "kind": "variable", "doc": "

the i-th block of the sample

\n", "annotation": ": int"}, "bioimageio.core.block_meta.BlockMeta.blocks_in_sample": {"fullname": "bioimageio.core.block_meta.BlockMeta.blocks_in_sample", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.blocks_in_sample", "kind": "variable", "doc": "

total number of blocks in the sample

\n", "annotation": ": int"}, "bioimageio.core.block_meta.BlockMeta.shape": {"fullname": "bioimageio.core.block_meta.BlockMeta.shape", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.shape", "kind": "variable", "doc": "

axis lengths of the block

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, int]"}, "bioimageio.core.block_meta.BlockMeta.padding": {"fullname": "bioimageio.core.block_meta.BlockMeta.padding", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.padding", "kind": "variable", "doc": "

padding to realize the halo at the sample edge\nwhere we cannot simply enlarge the inner slice

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.PadWidth]"}, "bioimageio.core.block_meta.BlockMeta.outer_slice": {"fullname": "bioimageio.core.block_meta.BlockMeta.outer_slice", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.outer_slice", "kind": "variable", "doc": "

slice of the outer block (without padding) wrt the sample

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.SliceInfo]"}, "bioimageio.core.block_meta.BlockMeta.inner_shape": {"fullname": "bioimageio.core.block_meta.BlockMeta.inner_shape", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.inner_shape", "kind": "variable", "doc": "

axis lengths of the inner region (without halo)

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, int]"}, "bioimageio.core.block_meta.BlockMeta.local_slice": {"fullname": "bioimageio.core.block_meta.BlockMeta.local_slice", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.local_slice", "kind": "variable", "doc": "

inner slice wrt the block, not the sample

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.SliceInfo]"}, "bioimageio.core.block_meta.BlockMeta.dims": {"fullname": "bioimageio.core.block_meta.BlockMeta.dims", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.dims", "kind": "variable", "doc": "

\n", "annotation": ": Collection[bioimageio.spec.model.v0_5.AxisId]"}, "bioimageio.core.block_meta.BlockMeta.tagged_shape": {"fullname": "bioimageio.core.block_meta.BlockMeta.tagged_shape", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.tagged_shape", "kind": "variable", "doc": "

alias for shape

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, int]"}, "bioimageio.core.block_meta.BlockMeta.inner_slice_wo_overlap": {"fullname": "bioimageio.core.block_meta.BlockMeta.inner_slice_wo_overlap", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.inner_slice_wo_overlap", "kind": "variable", "doc": "

subslice of the inner slice, such that all inner_slice_wo_overlap can be\nstiched together trivially to form the original sample.

\n\n

This can also be used to calculate statistics\nwithout overrepresenting block edge regions.

\n"}, "bioimageio.core.block_meta.BlockMeta.get_transformed": {"fullname": "bioimageio.core.block_meta.BlockMeta.get_transformed", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.get_transformed", "kind": "function", "doc": "

\n", "signature": "(\tself,\tnew_axes: Mapping[bioimageio.spec.model.v0_5.AxisId, Union[bioimageio.core.block_meta.LinearAxisTransform, int]]) -> Self:", "funcdef": "def"}, "bioimageio.core.block_meta.split_shape_into_blocks": {"fullname": "bioimageio.core.block_meta.split_shape_into_blocks", "modulename": "bioimageio.core.block_meta", "qualname": "split_shape_into_blocks", "kind": "function", "doc": "

\n", "signature": "(\tshape: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\tblock_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\thalo: Mapping[bioimageio.spec.model.v0_5.AxisId, Union[int, Tuple[int, int], bioimageio.core.common.Halo]],\tstride: Optional[Mapping[bioimageio.spec.model.v0_5.AxisId, int]] = None) -> Tuple[int, Generator[bioimageio.core.block_meta.BlockMeta, Any, NoneType]]:", "funcdef": "def"}, "bioimageio.core.block_meta.split_multiple_shapes_into_blocks": {"fullname": "bioimageio.core.block_meta.split_multiple_shapes_into_blocks", "modulename": "bioimageio.core.block_meta", "qualname": "split_multiple_shapes_into_blocks", "kind": "function", "doc": "

\n", "signature": "(\tshapes: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tblock_shapes: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\t*,\thalo: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, Union[int, Tuple[int, int], bioimageio.core.common.Halo]]],\tstrides: Optional[Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]] = None,\tbroadcast: bool = False) -> Tuple[int, Iterable[Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.block_meta.BlockMeta]]]:", "funcdef": "def"}, "bioimageio.core.cli": {"fullname": "bioimageio.core.cli", "modulename": "bioimageio.core.cli", "kind": "module", "doc": "

bioimageio CLI

\n\n

Note: Some docstrings use a hair space '\u200a'\n to place the added '(default: ...)' on a new line.

\n"}, "bioimageio.core.cli.yaml": {"fullname": "bioimageio.core.cli.yaml", "modulename": "bioimageio.core.cli", "qualname": "yaml", "kind": "variable", "doc": "

\n", "default_value": "<ruyaml.main.YAML object>"}, "bioimageio.core.cli.CmdBase": {"fullname": "bioimageio.core.cli.CmdBase", "modulename": "bioimageio.core.cli", "qualname": "CmdBase", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.9/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of the class variables defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The synthesized __init__ [Signature][inspect.Signature] of the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The core schema of the model.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a [`RootModel`][pydantic.root_model.RootModel].\n__pydantic_serializer__: The `pydantic-core` `SchemaSerializer` used to dump instances of the model.\n__pydantic_validator__: The `pydantic-core` `SchemaValidator` used to validate instances of the model.\n\n__pydantic_extra__: A dictionary containing extra values, if [`extra`][pydantic.config.ConfigDict.extra]\n    is set to `'allow'`.\n__pydantic_fields_set__: The names of fields explicitly set during instantiation.\n__pydantic_private__: Values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "bioimageio.core.cli.CmdBase.model_config": {"fullname": "bioimageio.core.cli.CmdBase.model_config", "modulename": "bioimageio.core.cli", "qualname": "CmdBase.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'use_attribute_docstrings': True}"}, "bioimageio.core.cli.CmdBase.model_fields": {"fullname": "bioimageio.core.cli.CmdBase.model_fields", "modulename": "bioimageio.core.cli", "qualname": "CmdBase.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{}"}, "bioimageio.core.cli.CmdBase.model_computed_fields": {"fullname": "bioimageio.core.cli.CmdBase.model_computed_fields", "modulename": "bioimageio.core.cli", "qualname": "CmdBase.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.cli.ArgMixin": {"fullname": "bioimageio.core.cli.ArgMixin", "modulename": "bioimageio.core.cli", "qualname": "ArgMixin", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.9/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of the class variables defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The synthesized __init__ [Signature][inspect.Signature] of the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The core schema of the model.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a [`RootModel`][pydantic.root_model.RootModel].\n__pydantic_serializer__: The `pydantic-core` `SchemaSerializer` used to dump instances of the model.\n__pydantic_validator__: The `pydantic-core` `SchemaValidator` used to validate instances of the model.\n\n__pydantic_extra__: A dictionary containing extra values, if [`extra`][pydantic.config.ConfigDict.extra]\n    is set to `'allow'`.\n__pydantic_fields_set__: The names of fields explicitly set during instantiation.\n__pydantic_private__: Values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "bioimageio.core.cli.ArgMixin.model_config": {"fullname": "bioimageio.core.cli.ArgMixin.model_config", "modulename": "bioimageio.core.cli", "qualname": "ArgMixin.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'use_attribute_docstrings': True}"}, "bioimageio.core.cli.ArgMixin.model_fields": {"fullname": "bioimageio.core.cli.ArgMixin.model_fields", "modulename": "bioimageio.core.cli", "qualname": "ArgMixin.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{}"}, "bioimageio.core.cli.ArgMixin.model_computed_fields": {"fullname": "bioimageio.core.cli.ArgMixin.model_computed_fields", "modulename": "bioimageio.core.cli", "qualname": "ArgMixin.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.cli.WithSource": {"fullname": "bioimageio.core.cli.WithSource", "modulename": "bioimageio.core.cli", "qualname": "WithSource", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.9/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of the class variables defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The synthesized __init__ [Signature][inspect.Signature] of the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The core schema of the model.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a [`RootModel`][pydantic.root_model.RootModel].\n__pydantic_serializer__: The `pydantic-core` `SchemaSerializer` used to dump instances of the model.\n__pydantic_validator__: The `pydantic-core` `SchemaValidator` used to validate instances of the model.\n\n__pydantic_extra__: A dictionary containing extra values, if [`extra`][pydantic.config.ConfigDict.extra]\n    is set to `'allow'`.\n__pydantic_fields_set__: The names of fields explicitly set during instantiation.\n__pydantic_private__: Values of private attributes set on the model instance.\n
\n", "bases": "ArgMixin"}, "bioimageio.core.cli.WithSource.source": {"fullname": "bioimageio.core.cli.WithSource.source", "modulename": "bioimageio.core.cli", "qualname": "WithSource.source", "kind": "variable", "doc": "

Url/path to a bioimageio.yaml/rdf.yaml file\nor a bioimage.io resource identifier, e.g. 'affable-shark'

\n", "annotation": ": Annotated[str, <class 'pydantic_settings.sources._CliPositionalArg'>]"}, "bioimageio.core.cli.WithSource.descr": {"fullname": "bioimageio.core.cli.WithSource.descr", "modulename": "bioimageio.core.cli", "qualname": "WithSource.descr", "kind": "variable", "doc": "

\n"}, "bioimageio.core.cli.WithSource.descr_id": {"fullname": "bioimageio.core.cli.WithSource.descr_id", "modulename": "bioimageio.core.cli", "qualname": "WithSource.descr_id", "kind": "variable", "doc": "

a more user-friendly description id\n(replacing legacy ids with their nicknames)

\n", "annotation": ": str"}, "bioimageio.core.cli.WithSource.model_config": {"fullname": "bioimageio.core.cli.WithSource.model_config", "modulename": "bioimageio.core.cli", "qualname": "WithSource.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'use_attribute_docstrings': True}"}, "bioimageio.core.cli.WithSource.model_fields": {"fullname": "bioimageio.core.cli.WithSource.model_fields", "modulename": "bioimageio.core.cli", "qualname": "WithSource.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'source': FieldInfo(annotation=str, required=True, description="Url/path to a bioimageio.yaml/rdf.yaml file\\nor a bioimage.io resource identifier, e.g. 'affable-shark'", metadata=[<class 'pydantic_settings.sources._CliPositionalArg'>])}"}, "bioimageio.core.cli.WithSource.model_computed_fields": {"fullname": "bioimageio.core.cli.WithSource.model_computed_fields", "modulename": "bioimageio.core.cli", "qualname": "WithSource.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.cli.ValidateFormatCmd": {"fullname": "bioimageio.core.cli.ValidateFormatCmd", "modulename": "bioimageio.core.cli", "qualname": "ValidateFormatCmd", "kind": "class", "doc": "

bioimageio-validate-format - validate the meta data format of a bioimageio resource.

\n", "bases": "CmdBase, WithSource"}, "bioimageio.core.cli.ValidateFormatCmd.run": {"fullname": "bioimageio.core.cli.ValidateFormatCmd.run", "modulename": "bioimageio.core.cli", "qualname": "ValidateFormatCmd.run", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.cli.ValidateFormatCmd.model_config": {"fullname": "bioimageio.core.cli.ValidateFormatCmd.model_config", "modulename": "bioimageio.core.cli", "qualname": "ValidateFormatCmd.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'use_attribute_docstrings': True}"}, "bioimageio.core.cli.ValidateFormatCmd.model_fields": {"fullname": "bioimageio.core.cli.ValidateFormatCmd.model_fields", "modulename": "bioimageio.core.cli", "qualname": "ValidateFormatCmd.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'source': FieldInfo(annotation=str, required=True, description="Url/path to a bioimageio.yaml/rdf.yaml file\\nor a bioimage.io resource identifier, e.g. 'affable-shark'", metadata=[<class 'pydantic_settings.sources._CliPositionalArg'>])}"}, "bioimageio.core.cli.ValidateFormatCmd.model_computed_fields": {"fullname": "bioimageio.core.cli.ValidateFormatCmd.model_computed_fields", "modulename": "bioimageio.core.cli", "qualname": "ValidateFormatCmd.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.cli.TestCmd": {"fullname": "bioimageio.core.cli.TestCmd", "modulename": "bioimageio.core.cli", "qualname": "TestCmd", "kind": "class", "doc": "

bioimageio-test - Test a bioimageio resource (beyond meta data formatting)

\n", "bases": "CmdBase, WithSource"}, "bioimageio.core.cli.TestCmd.weight_format": {"fullname": "bioimageio.core.cli.TestCmd.weight_format", "modulename": "bioimageio.core.cli", "qualname": "TestCmd.weight_format", "kind": "variable", "doc": "

The weight format to limit testing to.

\n\n

(only relevant for model resources)

\n", "annotation": ": Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript', 'all']"}, "bioimageio.core.cli.TestCmd.devices": {"fullname": "bioimageio.core.cli.TestCmd.devices", "modulename": "bioimageio.core.cli", "qualname": "TestCmd.devices", "kind": "variable", "doc": "

Device(s) to use for testing

\n", "annotation": ": Union[str, Sequence[str], NoneType]"}, "bioimageio.core.cli.TestCmd.decimal": {"fullname": "bioimageio.core.cli.TestCmd.decimal", "modulename": "bioimageio.core.cli", "qualname": "TestCmd.decimal", "kind": "variable", "doc": "

Precision for numerical comparisons

\n", "annotation": ": int"}, "bioimageio.core.cli.TestCmd.run": {"fullname": "bioimageio.core.cli.TestCmd.run", "modulename": "bioimageio.core.cli", "qualname": "TestCmd.run", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.cli.TestCmd.model_config": {"fullname": "bioimageio.core.cli.TestCmd.model_config", "modulename": "bioimageio.core.cli", "qualname": "TestCmd.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'use_attribute_docstrings': True}"}, "bioimageio.core.cli.TestCmd.model_fields": {"fullname": "bioimageio.core.cli.TestCmd.model_fields", "modulename": "bioimageio.core.cli", "qualname": "TestCmd.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'source': FieldInfo(annotation=str, required=True, description="Url/path to a bioimageio.yaml/rdf.yaml file\\nor a bioimage.io resource identifier, e.g. 'affable-shark'", metadata=[<class 'pydantic_settings.sources._CliPositionalArg'>]), 'weight_format': FieldInfo(annotation=Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript', 'all'], required=False, default='all', description='The weight format to limit testing to.\\n\\n(only relevant for model resources)'), 'devices': FieldInfo(annotation=Union[str, Sequence[str], NoneType], required=False, default=None, description='Device(s) to use for testing'), 'decimal': FieldInfo(annotation=int, required=False, default=4, description='Precision for numerical comparisons')}"}, "bioimageio.core.cli.TestCmd.model_computed_fields": {"fullname": "bioimageio.core.cli.TestCmd.model_computed_fields", "modulename": "bioimageio.core.cli", "qualname": "TestCmd.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.cli.PackageCmd": {"fullname": "bioimageio.core.cli.PackageCmd", "modulename": "bioimageio.core.cli", "qualname": "PackageCmd", "kind": "class", "doc": "

bioimageio-package - save a resource's metadata with its associated files.

\n", "bases": "CmdBase, WithSource"}, "bioimageio.core.cli.PackageCmd.path": {"fullname": "bioimageio.core.cli.PackageCmd.path", "modulename": "bioimageio.core.cli", "qualname": "PackageCmd.path", "kind": "variable", "doc": "

The path to write the (zipped) package to.\nIf it does not have a .zip suffix\nthis command will save the package as an unzipped folder instead.

\n", "annotation": ": Annotated[pathlib.Path, <class 'pydantic_settings.sources._CliPositionalArg'>]"}, "bioimageio.core.cli.PackageCmd.weight_format": {"fullname": "bioimageio.core.cli.PackageCmd.weight_format", "modulename": "bioimageio.core.cli", "qualname": "PackageCmd.weight_format", "kind": "variable", "doc": "

The weight format to include in the package (for model descriptions only).

\n", "annotation": ": Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript', 'all']"}, "bioimageio.core.cli.PackageCmd.run": {"fullname": "bioimageio.core.cli.PackageCmd.run", "modulename": "bioimageio.core.cli", "qualname": "PackageCmd.run", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.cli.PackageCmd.model_config": {"fullname": "bioimageio.core.cli.PackageCmd.model_config", "modulename": "bioimageio.core.cli", "qualname": "PackageCmd.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'use_attribute_docstrings': True}"}, "bioimageio.core.cli.PackageCmd.model_fields": {"fullname": "bioimageio.core.cli.PackageCmd.model_fields", "modulename": "bioimageio.core.cli", "qualname": "PackageCmd.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'source': FieldInfo(annotation=str, required=True, description="Url/path to a bioimageio.yaml/rdf.yaml file\\nor a bioimage.io resource identifier, e.g. 'affable-shark'", metadata=[<class 'pydantic_settings.sources._CliPositionalArg'>]), 'path': FieldInfo(annotation=Path, required=True, description='The path to write the (zipped) package to.\\nIf it does not have a `.zip` suffix\\nthis command will save the package as an unzipped folder instead.', metadata=[<class 'pydantic_settings.sources._CliPositionalArg'>]), 'weight_format': FieldInfo(annotation=Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript', 'all'], required=False, default='all', description='The weight format to include in the package (for model descriptions only).')}"}, "bioimageio.core.cli.PackageCmd.model_computed_fields": {"fullname": "bioimageio.core.cli.PackageCmd.model_computed_fields", "modulename": "bioimageio.core.cli", "qualname": "PackageCmd.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.cli.PredictCmd": {"fullname": "bioimageio.core.cli.PredictCmd", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd", "kind": "class", "doc": "

bioimageio-predict - Run inference on your data with a bioimage.io model.

\n", "bases": "CmdBase, WithSource"}, "bioimageio.core.cli.PredictCmd.inputs": {"fullname": "bioimageio.core.cli.PredictCmd.inputs", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.inputs", "kind": "variable", "doc": "

Model input sample paths (for each input tensor)

\n\n

The input paths are expected to have shape...

\n\n
    \n
  • (n_samples,) or (n_samples,1) for models expecting a single input tensor
    • \n
  • (n_samples,) containing the substring '{input_id}', or
    • \n
  • (n_samples, n_model_inputs) to provide each input tensor path explicitly.
    • \n
\n\n

All substrings that are replaced by metadata from the model description:

\n\n
    \n
  • '{model_id}'
    • \n
  • '{input_id}'
    • \n
\n\n

Example inputs to process sample 'a' and 'b'\nfor a model expecting a 'raw' and a 'mask' input tensor:\n--inputs=\"[[\"a_raw.tif\",\"a_mask.tif\"],[\"b_raw.tif\",\"b_mask.tif\"]]\"\n(Note that JSON double quotes need to be escaped.)

\n\n

Alternatively a bioimageio-cli.yaml (or bioimageio-cli.json) file\nmay provide the arguments, e.g.:

\n\n
\n
inputs:\n- [a_raw.tif, a_mask.tif]\n- [b_raw.tif, b_mask.tif]\n
\n
\n\n

.npy and any file extension supported by imageio are supported.\n Aavailable formats are listed at\nhttps://imageio.readthedocs.io/en/stable/formats/index.html#all-formats.\nSome formats have additional dependencies.

\n", "annotation": ": Annotated[Sequence[Union[str, Annotated[Tuple[str, ...], MinLen(min_length=1)]]], MinLen(min_length=1)]"}, "bioimageio.core.cli.PredictCmd.outputs": {"fullname": "bioimageio.core.cli.PredictCmd.outputs", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.outputs", "kind": "variable", "doc": "

Model output path pattern (per output tensor)

\n\n

All substrings that are replaced:

\n\n
    \n
  • '{model_id}' (from model description)
    • \n
  • '{output_id}' (from model description)
    • \n
  • '{sample_id}' (extracted from input paths)
    • \n
\n", "annotation": ": Union[str, Annotated[Tuple[str, ...], MinLen(min_length=1)]]"}, "bioimageio.core.cli.PredictCmd.overwrite": {"fullname": "bioimageio.core.cli.PredictCmd.overwrite", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.overwrite", "kind": "variable", "doc": "

allow overwriting existing output files

\n", "annotation": ": bool"}, "bioimageio.core.cli.PredictCmd.blockwise": {"fullname": "bioimageio.core.cli.PredictCmd.blockwise", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.blockwise", "kind": "variable", "doc": "

process inputs blockwise

\n", "annotation": ": bool"}, "bioimageio.core.cli.PredictCmd.stats": {"fullname": "bioimageio.core.cli.PredictCmd.stats", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.stats", "kind": "variable", "doc": "

path to dataset statistics\n(will be written if it does not exist,\nbut the model requires statistical dataset measures)

\n", "annotation": ": pathlib.Path"}, "bioimageio.core.cli.PredictCmd.preview": {"fullname": "bioimageio.core.cli.PredictCmd.preview", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.preview", "kind": "variable", "doc": "

preview which files would be processed\nand what outputs would be generated.

\n", "annotation": ": bool"}, "bioimageio.core.cli.PredictCmd.weight_format": {"fullname": "bioimageio.core.cli.PredictCmd.weight_format", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.weight_format", "kind": "variable", "doc": "

The weight format to use.

\n", "annotation": ": Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript', 'any']"}, "bioimageio.core.cli.PredictCmd.example": {"fullname": "bioimageio.core.cli.PredictCmd.example", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.example", "kind": "variable", "doc": "

generate and run an example

\n\n
    \n
  1. downloads example model inputs
    2. \n
  2. creates a {model_id}_example folder
    3. \n
  3. writes input arguments to {model_id}_example/bioimageio-cli.yaml
    4. \n
  4. executes a preview dry-run
    5. \n
  5. executes prediction with example input
    6. \n
\n", "annotation": ": bool"}, "bioimageio.core.cli.PredictCmd.run": {"fullname": "bioimageio.core.cli.PredictCmd.run", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.run", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.cli.PredictCmd.model_config": {"fullname": "bioimageio.core.cli.PredictCmd.model_config", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'use_attribute_docstrings': True}"}, "bioimageio.core.cli.PredictCmd.model_fields": {"fullname": "bioimageio.core.cli.PredictCmd.model_fields", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'source': FieldInfo(annotation=str, required=True, description="Url/path to a bioimageio.yaml/rdf.yaml file\\nor a bioimage.io resource identifier, e.g. 'affable-shark'", metadata=[<class 'pydantic_settings.sources._CliPositionalArg'>]), 'inputs': FieldInfo(annotation=Sequence[Union[str, Annotated[Tuple[str, ...], MinLen]]], required=False, default=('{input_id}/001.tif',), description='Model input sample paths (for each input tensor)\\n\\nThe input paths are expected to have shape...\\n - (n_samples,) or (n_samples,1) for models expecting a single input tensor\\n - (n_samples,) containing the substring \\'{input_id}\\', or\\n - (n_samples, n_model_inputs) to provide each input tensor path explicitly.\\n\\nAll substrings that are replaced by metadata from the model description:\\n- \\'{model_id}\\'\\n- \\'{input_id}\\'\\n\\nExample inputs to process sample \\'a\\' and \\'b\\'\\nfor a model expecting a \\'raw\\' and a \\'mask\\' input tensor:\\n--inputs="[["a_raw.tif","a_mask.tif"],["b_raw.tif","b_mask.tif"]]"\\n(Note that JSON double quotes need to be escaped.)\\n\\nAlternatively a `bioimageio-cli.yaml` (or `bioimageio-cli.json`) file\\nmay provide the arguments, e.g.:\\n```yaml\\ninputs:\\n- [a_raw.tif, a_mask.tif]\\n- [b_raw.tif, b_mask.tif]\\n```\\n\\n`.npy` and any file extension supported by imageio are supported.\\n Aavailable formats are listed at\\nhttps://imageio.readthedocs.io/en/stable/formats/index.html#all-formats.\\nSome formats have additional dependencies.\\n\\n\\u200a', metadata=[MinLen(min_length=1)]), 'outputs': FieldInfo(annotation=Union[str, Annotated[Tuple[str, ...], MinLen]], required=False, default='outputs_{model_id}/{output_id}/{sample_id}.tif', description="Model output path pattern (per output tensor)\\n\\nAll substrings that are replaced:\\n- '{model_id}' (from model description)\\n- '{output_id}' (from model description)\\n- '{sample_id}' (extracted from input paths)\\n\\n\\u200a"), 'overwrite': FieldInfo(annotation=bool, required=False, default=False, description='allow overwriting existing output files'), 'blockwise': FieldInfo(annotation=bool, required=False, default=False, description='process inputs blockwise'), 'stats': FieldInfo(annotation=Path, required=False, default=PosixPath('dataset_statistics.json'), description='path to dataset statistics\\n(will be written if it does not exist,\\nbut the model requires statistical dataset measures)\\n\\u200a'), 'preview': FieldInfo(annotation=bool, required=False, default=False, description='preview which files would be processed\\nand what outputs would be generated.'), 'weight_format': FieldInfo(annotation=Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript', 'any'], required=False, default='any', description='The weight format to use.'), 'example': FieldInfo(annotation=bool, required=False, default=False, description='generate and run an example\\n\\n1. downloads example model inputs\\n2. creates a `{model_id}_example` folder\\n3. writes input arguments to `{model_id}_example/bioimageio-cli.yaml`\\n4. executes a preview dry-run\\n5. executes prediction with example input\\n\\n\\u200a')}"}, "bioimageio.core.cli.PredictCmd.model_computed_fields": {"fullname": "bioimageio.core.cli.PredictCmd.model_computed_fields", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.cli.JSON_FILE": {"fullname": "bioimageio.core.cli.JSON_FILE", "modulename": "bioimageio.core.cli", "qualname": "JSON_FILE", "kind": "variable", "doc": "

\n", "default_value": "'bioimageio-cli.json'"}, "bioimageio.core.cli.YAML_FILE": {"fullname": "bioimageio.core.cli.YAML_FILE", "modulename": "bioimageio.core.cli", "qualname": "YAML_FILE", "kind": "variable", "doc": "

\n", "default_value": "'bioimageio-cli.yaml'"}, "bioimageio.core.cli.Bioimageio": {"fullname": "bioimageio.core.cli.Bioimageio", "modulename": "bioimageio.core.cli", "qualname": "Bioimageio", "kind": "class", "doc": "

bioimageio - CLI for bioimage.io resources \ud83e\udd92

\n\n

library versions:\n bioimageio.core 0.6.10\n bioimageio.spec 0.6.10

\n\n

spec format versions:\n model RDF 0.5.3\n dataset RDF 0.3.0\n notebook RDF 0.3.0

\n", "bases": "pydantic_settings.main.BaseSettings"}, "bioimageio.core.cli.Bioimageio.model_config": {"fullname": "bioimageio.core.cli.Bioimageio.model_config", "modulename": "bioimageio.core.cli", "qualname": "Bioimageio.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "default_value": "{'extra': 'forbid', 'arbitrary_types_allowed': True, 'validate_default': True, 'case_sensitive': False, 'env_prefix': '', 'nested_model_default_partial_update': False, 'env_file': None, 'env_file_encoding': None, 'env_ignore_empty': False, 'env_nested_delimiter': None, 'env_parse_none_str': None, 'env_parse_enums': None, 'cli_prog_name': 'bioimageio', 'cli_parse_args': True, 'cli_parse_none_str': None, 'cli_hide_none_type': False, 'cli_avoid_json': False, 'cli_enforce_required': False, 'cli_use_class_docs_for_groups': True, 'cli_exit_on_error': True, 'cli_prefix': '', 'cli_flag_prefix_char': '-', 'cli_implicit_flags': False, 'cli_ignore_unknown_args': False, 'json_file': 'bioimageio-cli.json', 'json_file_encoding': None, 'yaml_file': 'bioimageio-cli.yaml', 'yaml_file_encoding': None, 'toml_file': None, 'secrets_dir': None, 'protected_namespaces': ('model_', 'settings_'), 'use_attribute_docstrings': True}"}, "bioimageio.core.cli.Bioimageio.validate_format": {"fullname": "bioimageio.core.cli.Bioimageio.validate_format", "modulename": "bioimageio.core.cli", "qualname": "Bioimageio.validate_format", "kind": "variable", "doc": "

Check a resource's metadata format

\n", "annotation": ": Annotated[Optional[bioimageio.core.cli.ValidateFormatCmd], <class 'pydantic_settings.sources._CliSubCommand'>]"}, "bioimageio.core.cli.Bioimageio.test": {"fullname": "bioimageio.core.cli.Bioimageio.test", "modulename": "bioimageio.core.cli", "qualname": "Bioimageio.test", "kind": "variable", "doc": "

Test a bioimageio resource (beyond meta data formatting)

\n", "annotation": ": Annotated[Optional[bioimageio.core.cli.TestCmd], <class 'pydantic_settings.sources._CliSubCommand'>]"}, "bioimageio.core.cli.Bioimageio.package": {"fullname": "bioimageio.core.cli.Bioimageio.package", "modulename": "bioimageio.core.cli", "qualname": "Bioimageio.package", "kind": "variable", "doc": "

Package a resource

\n", "annotation": ": Annotated[Optional[bioimageio.core.cli.PackageCmd], <class 'pydantic_settings.sources._CliSubCommand'>]"}, "bioimageio.core.cli.Bioimageio.predict": {"fullname": "bioimageio.core.cli.Bioimageio.predict", "modulename": "bioimageio.core.cli", "qualname": "Bioimageio.predict", "kind": "variable", "doc": "

Predict with a model resource

\n", "annotation": ": Annotated[Optional[bioimageio.core.cli.PredictCmd], <class 'pydantic_settings.sources._CliSubCommand'>]"}, "bioimageio.core.cli.Bioimageio.settings_customise_sources": {"fullname": "bioimageio.core.cli.Bioimageio.settings_customise_sources", "modulename": "bioimageio.core.cli", "qualname": "Bioimageio.settings_customise_sources", "kind": "function", "doc": "

Define the sources and their order for loading the settings values.

\n\n

Args:\n settings_cls: The Settings class.\n init_settings: The InitSettingsSource instance.\n env_settings: The EnvSettingsSource instance.\n dotenv_settings: The DotEnvSettingsSource instance.\n file_secret_settings: The SecretsSettingsSource instance.

\n\n

Returns:\n A tuple containing the sources and their order for loading the settings values.

\n", "signature": "(\tcls,\tsettings_cls: Type[pydantic_settings.main.BaseSettings],\tinit_settings: pydantic_settings.sources.PydanticBaseSettingsSource,\tenv_settings: pydantic_settings.sources.PydanticBaseSettingsSource,\tdotenv_settings: pydantic_settings.sources.PydanticBaseSettingsSource,\tfile_secret_settings: pydantic_settings.sources.PydanticBaseSettingsSource) -> Tuple[pydantic_settings.sources.PydanticBaseSettingsSource, ...]:", "funcdef": "def"}, "bioimageio.core.cli.Bioimageio.run": {"fullname": "bioimageio.core.cli.Bioimageio.run", "modulename": "bioimageio.core.cli", "qualname": "Bioimageio.run", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.cli.Bioimageio.model_fields": {"fullname": "bioimageio.core.cli.Bioimageio.model_fields", "modulename": "bioimageio.core.cli", "qualname": "Bioimageio.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'validate_format': FieldInfo(annotation=Union[ValidateFormatCmd, NoneType], required=True, description="Check a resource's metadata format", metadata=[<class 'pydantic_settings.sources._CliSubCommand'>]), 'test': FieldInfo(annotation=Union[TestCmd, NoneType], required=True, description='Test a bioimageio resource (beyond meta data formatting)', metadata=[<class 'pydantic_settings.sources._CliSubCommand'>]), 'package': FieldInfo(annotation=Union[PackageCmd, NoneType], required=True, description='Package a resource', metadata=[<class 'pydantic_settings.sources._CliSubCommand'>]), 'predict': FieldInfo(annotation=Union[PredictCmd, NoneType], required=True, description='Predict with a model resource', metadata=[<class 'pydantic_settings.sources._CliSubCommand'>])}"}, "bioimageio.core.cli.Bioimageio.model_computed_fields": {"fullname": "bioimageio.core.cli.Bioimageio.model_computed_fields", "modulename": "bioimageio.core.cli", "qualname": "Bioimageio.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.commands": {"fullname": "bioimageio.core.commands", "modulename": "bioimageio.core.commands", "kind": "module", "doc": "

These functions implement the logic of the bioimageio command line interface\ndefined in the cli module.

\n"}, "bioimageio.core.commands.WeightFormatArgAll": {"fullname": "bioimageio.core.commands.WeightFormatArgAll", "modulename": "bioimageio.core.commands", "qualname": "WeightFormatArgAll", "kind": "variable", "doc": "

\n", "default_value": "typing.Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript', 'all']"}, "bioimageio.core.commands.WeightFormatArgAny": {"fullname": "bioimageio.core.commands.WeightFormatArgAny", "modulename": "bioimageio.core.commands", "qualname": "WeightFormatArgAny", "kind": "variable", "doc": "

\n", "default_value": "typing.Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript', 'any']"}, "bioimageio.core.commands.test": {"fullname": "bioimageio.core.commands.test", "modulename": "bioimageio.core.commands", "qualname": "test", "kind": "function", "doc": "

test a bioimageio resource

\n\n

Args:\n source: Path or URL to the bioimageio resource description file\n (bioimageio.yaml or rdf.yaml) or to a zipped resource\n weight_format: (model only) The weight format to use\n devices: Device(s) to use for testing\n decimal: Precision for numerical comparisons

\n", "signature": "(\tdescr: Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.spec._internal.common_nodes.InvalidDescr],\t*,\tweight_format: Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript', 'all'] = 'all',\tdevices: Union[str, Sequence[str], NoneType] = None,\tdecimal: int = 4):", "funcdef": "def"}, "bioimageio.core.commands.validate_format": {"fullname": "bioimageio.core.commands.validate_format", "modulename": "bioimageio.core.commands", "qualname": "validate_format", "kind": "function", "doc": "

validate the meta data format of a bioimageio resource

\n\n

Args:\n descr: a bioimageio resource description

\n", "signature": "(\tdescr: Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.spec._internal.common_nodes.InvalidDescr]):", "funcdef": "def"}, "bioimageio.core.commands.package": {"fullname": "bioimageio.core.commands.package", "modulename": "bioimageio.core.commands", "qualname": "package", "kind": "function", "doc": "

Save a resource's metadata with its associated files.

\n\n

Note: If path does not have a .zip suffix this command will save the\n package as an unzipped folder instead.

\n\n

Args:\n descr: a bioimageio resource description\n path: output path\n weight-format: include only this single weight-format (if not 'all').

\n", "signature": "(\tdescr: Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]],\tpath: pathlib.Path,\t*,\tweight_format: Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript', 'all'] = 'all'):", "funcdef": "def"}, "bioimageio.core.common": {"fullname": "bioimageio.core.common", "modulename": "bioimageio.core.common", "kind": "module", "doc": "

\n"}, "bioimageio.core.common.DTypeStr": {"fullname": "bioimageio.core.common.DTypeStr", "modulename": "bioimageio.core.common", "qualname": "DTypeStr", "kind": "variable", "doc": "

\n", "default_value": "typing.Literal['bool', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64']"}, "bioimageio.core.common.CropWidth": {"fullname": "bioimageio.core.common.CropWidth", "modulename": "bioimageio.core.common", "qualname": "CropWidth", "kind": "class", "doc": "

_LeftRight(left, right)

\n", "bases": "typing.NamedTuple"}, "bioimageio.core.common.CropWidth.__init__": {"fullname": "bioimageio.core.common.CropWidth.__init__", "modulename": "bioimageio.core.common", "qualname": "CropWidth.__init__", "kind": "function", "doc": "

Create new instance of _LeftRight(left, right)

\n", "signature": "(left: int, right: int)"}, "bioimageio.core.common.CropWidthLike": {"fullname": "bioimageio.core.common.CropWidthLike", "modulename": "bioimageio.core.common", "qualname": "CropWidthLike", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[int, typing.Tuple[int, int], bioimageio.core.common.CropWidth]"}, "bioimageio.core.common.CropWhere": {"fullname": "bioimageio.core.common.CropWhere", "modulename": "bioimageio.core.common", "qualname": "CropWhere", "kind": "variable", "doc": "

\n", "default_value": "typing.Literal['left', 'right', 'left_and_right']"}, "bioimageio.core.common.Halo": {"fullname": "bioimageio.core.common.Halo", "modulename": "bioimageio.core.common", "qualname": "Halo", "kind": "class", "doc": "

_LeftRight(left, right)

\n", "bases": "typing.NamedTuple"}, "bioimageio.core.common.Halo.__init__": {"fullname": "bioimageio.core.common.Halo.__init__", "modulename": "bioimageio.core.common", "qualname": "Halo.__init__", "kind": "function", "doc": "

Create new instance of _LeftRight(left, right)

\n", "signature": "(left: int, right: int)"}, "bioimageio.core.common.HaloLike": {"fullname": "bioimageio.core.common.HaloLike", "modulename": "bioimageio.core.common", "qualname": "HaloLike", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[int, typing.Tuple[int, int], bioimageio.core.common.Halo]"}, "bioimageio.core.common.OverlapWidth": {"fullname": "bioimageio.core.common.OverlapWidth", "modulename": "bioimageio.core.common", "qualname": "OverlapWidth", "kind": "class", "doc": "

_LeftRight(left, right)

\n", "bases": "typing.NamedTuple"}, "bioimageio.core.common.OverlapWidth.__init__": {"fullname": "bioimageio.core.common.OverlapWidth.__init__", "modulename": "bioimageio.core.common", "qualname": "OverlapWidth.__init__", "kind": "function", "doc": "

Create new instance of _LeftRight(left, right)

\n", "signature": "(left: int, right: int)"}, "bioimageio.core.common.PadWidth": {"fullname": "bioimageio.core.common.PadWidth", "modulename": "bioimageio.core.common", "qualname": "PadWidth", "kind": "class", "doc": "

_LeftRight(left, right)

\n", "bases": "typing.NamedTuple"}, "bioimageio.core.common.PadWidth.__init__": {"fullname": "bioimageio.core.common.PadWidth.__init__", "modulename": "bioimageio.core.common", "qualname": "PadWidth.__init__", "kind": "function", "doc": "

Create new instance of _LeftRight(left, right)

\n", "signature": "(left: int, right: int)"}, "bioimageio.core.common.PadWidthLike": {"fullname": "bioimageio.core.common.PadWidthLike", "modulename": "bioimageio.core.common", "qualname": "PadWidthLike", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[int, typing.Tuple[int, int], bioimageio.core.common.PadWidth]"}, "bioimageio.core.common.PadMode": {"fullname": "bioimageio.core.common.PadMode", "modulename": "bioimageio.core.common", "qualname": "PadMode", "kind": "variable", "doc": "

\n", "default_value": "typing.Literal['edge', 'reflect', 'symmetric']"}, "bioimageio.core.common.PadWhere": {"fullname": "bioimageio.core.common.PadWhere", "modulename": "bioimageio.core.common", "qualname": "PadWhere", "kind": "variable", "doc": "

\n", "default_value": "typing.Literal['left', 'right', 'left_and_right']"}, "bioimageio.core.common.SliceInfo": {"fullname": "bioimageio.core.common.SliceInfo", "modulename": "bioimageio.core.common", "qualname": "SliceInfo", "kind": "class", "doc": "

SliceInfo(start, stop)

\n", "bases": "typing.NamedTuple"}, "bioimageio.core.common.SliceInfo.__init__": {"fullname": "bioimageio.core.common.SliceInfo.__init__", "modulename": "bioimageio.core.common", "qualname": "SliceInfo.__init__", "kind": "function", "doc": "

Create new instance of SliceInfo(start, stop)

\n", "signature": "(start: int, stop: int)"}, "bioimageio.core.common.SliceInfo.start": {"fullname": "bioimageio.core.common.SliceInfo.start", "modulename": "bioimageio.core.common", "qualname": "SliceInfo.start", "kind": "variable", "doc": "

Alias for field number 0

\n", "annotation": ": int"}, "bioimageio.core.common.SliceInfo.stop": {"fullname": "bioimageio.core.common.SliceInfo.stop", "modulename": "bioimageio.core.common", "qualname": "SliceInfo.stop", "kind": "variable", "doc": "

Alias for field number 1

\n", "annotation": ": int"}, "bioimageio.core.common.SampleId": {"fullname": "bioimageio.core.common.SampleId", "modulename": "bioimageio.core.common", "qualname": "SampleId", "kind": "variable", "doc": "

\n", "default_value": "typing.Hashable"}, "bioimageio.core.common.MemberId": {"fullname": "bioimageio.core.common.MemberId", "modulename": "bioimageio.core.common", "qualname": "MemberId", "kind": "variable", "doc": "

\n", "default_value": "<class 'bioimageio.spec.model.v0_5.TensorId'>"}, "bioimageio.core.common.PerMember": {"fullname": "bioimageio.core.common.PerMember", "modulename": "bioimageio.core.common", "qualname": "PerMember", "kind": "variable", "doc": "

\n", "default_value": "typing.Mapping[bioimageio.spec.model.v0_5.TensorId, ~T]"}, "bioimageio.core.common.BlockIndex": {"fullname": "bioimageio.core.common.BlockIndex", "modulename": "bioimageio.core.common", "qualname": "BlockIndex", "kind": "variable", "doc": "

\n", "default_value": "<class 'int'>"}, "bioimageio.core.common.TotalNumberOfBlocks": {"fullname": "bioimageio.core.common.TotalNumberOfBlocks", "modulename": "bioimageio.core.common", "qualname": "TotalNumberOfBlocks", "kind": "variable", "doc": "

\n", "default_value": "<class 'int'>"}, "bioimageio.core.common.Frozen": {"fullname": "bioimageio.core.common.Frozen", "modulename": "bioimageio.core.common", "qualname": "Frozen", "kind": "variable", "doc": "

\n", "default_value": "<class 'mappingproxy'>"}, "bioimageio.core.dataset": {"fullname": "bioimageio.core.dataset", "modulename": "bioimageio.core.dataset", "kind": "module", "doc": "

\n"}, "bioimageio.core.dataset.Dataset": {"fullname": "bioimageio.core.dataset.Dataset", "modulename": "bioimageio.core.dataset", "qualname": "Dataset", "kind": "variable", "doc": "

\n", "default_value": "typing.Iterable[bioimageio.core.sample.Sample]"}, "bioimageio.core.digest_spec": {"fullname": "bioimageio.core.digest_spec", "modulename": "bioimageio.core.digest_spec", "kind": "module", "doc": "

\n"}, "bioimageio.core.digest_spec.import_callable": {"fullname": "bioimageio.core.digest_spec.import_callable", "modulename": "bioimageio.core.digest_spec", "qualname": "import_callable", "kind": "function", "doc": "

import a callable (e.g. a torch.nn.Module) from a spec node describing it

\n", "signature": "(\tnode: Union[bioimageio.spec.model.v0_4.CallableFromDepencency, bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr],\t/,\t**kwargs: Unpack[bioimageio.spec._internal.io.HashKwargs]) -> Callable[..., Any]:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_axes_infos": {"fullname": "bioimageio.core.digest_spec.get_axes_infos", "modulename": "bioimageio.core.digest_spec", "qualname": "get_axes_infos", "kind": "function", "doc": "

get a unified, simplified axis representation from spec axes

\n", "signature": "(\tio_descr: Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_4.OutputTensorDescr, bioimageio.spec.model.v0_5.InputTensorDescr, bioimageio.spec.model.v0_5.OutputTensorDescr]) -> List[bioimageio.core.axis.AxisInfo]:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_member_id": {"fullname": "bioimageio.core.digest_spec.get_member_id", "modulename": "bioimageio.core.digest_spec", "qualname": "get_member_id", "kind": "function", "doc": "

get the normalized tensor ID, usable as a sample member ID

\n", "signature": "(\ttensor_description: Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_4.OutputTensorDescr, bioimageio.spec.model.v0_5.InputTensorDescr, bioimageio.spec.model.v0_5.OutputTensorDescr]) -> bioimageio.spec.model.v0_5.TensorId:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_member_ids": {"fullname": "bioimageio.core.digest_spec.get_member_ids", "modulename": "bioimageio.core.digest_spec", "qualname": "get_member_ids", "kind": "function", "doc": "

get normalized tensor IDs to be used as sample member IDs

\n", "signature": "(\ttensor_descriptions: Sequence[Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_4.OutputTensorDescr, bioimageio.spec.model.v0_5.InputTensorDescr, bioimageio.spec.model.v0_5.OutputTensorDescr]]) -> List[bioimageio.spec.model.v0_5.TensorId]:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_test_inputs": {"fullname": "bioimageio.core.digest_spec.get_test_inputs", "modulename": "bioimageio.core.digest_spec", "qualname": "get_test_inputs", "kind": "function", "doc": "

returns a model's test input sample

\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]) -> bioimageio.core.sample.Sample:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_test_outputs": {"fullname": "bioimageio.core.digest_spec.get_test_outputs", "modulename": "bioimageio.core.digest_spec", "qualname": "get_test_outputs", "kind": "function", "doc": "

returns a model's test output sample

\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]) -> bioimageio.core.sample.Sample:", "funcdef": "def"}, "bioimageio.core.digest_spec.IO_SampleBlockMeta": {"fullname": "bioimageio.core.digest_spec.IO_SampleBlockMeta", "modulename": "bioimageio.core.digest_spec", "qualname": "IO_SampleBlockMeta", "kind": "class", "doc": "

IO_SampleBlockMeta(input, output)

\n", "bases": "typing.NamedTuple"}, "bioimageio.core.digest_spec.IO_SampleBlockMeta.__init__": {"fullname": "bioimageio.core.digest_spec.IO_SampleBlockMeta.__init__", "modulename": "bioimageio.core.digest_spec", "qualname": "IO_SampleBlockMeta.__init__", "kind": "function", "doc": "

Create new instance of IO_SampleBlockMeta(input, output)

\n", "signature": "(\tinput: ForwardRef('SampleBlockMeta'),\toutput: ForwardRef('SampleBlockMeta'))"}, "bioimageio.core.digest_spec.IO_SampleBlockMeta.input": {"fullname": "bioimageio.core.digest_spec.IO_SampleBlockMeta.input", "modulename": "bioimageio.core.digest_spec", "qualname": "IO_SampleBlockMeta.input", "kind": "variable", "doc": "

Alias for field number 0

\n", "annotation": ": bioimageio.core.sample.SampleBlockMeta"}, "bioimageio.core.digest_spec.IO_SampleBlockMeta.output": {"fullname": "bioimageio.core.digest_spec.IO_SampleBlockMeta.output", "modulename": "bioimageio.core.digest_spec", "qualname": "IO_SampleBlockMeta.output", "kind": "variable", "doc": "

Alias for field number 1

\n", "annotation": ": bioimageio.core.sample.SampleBlockMeta"}, "bioimageio.core.digest_spec.get_input_halo": {"fullname": "bioimageio.core.digest_spec.get_input_halo", "modulename": "bioimageio.core.digest_spec", "qualname": "get_input_halo", "kind": "function", "doc": "

returns which halo input tensors need to be divided into blocks with such that\noutput_halo can be cropped from their outputs without intorducing gaps.

\n", "signature": "(\tmodel: bioimageio.spec.model.v0_5.ModelDescr,\toutput_halo: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.Halo]]):", "funcdef": "def"}, "bioimageio.core.digest_spec.get_block_transform": {"fullname": "bioimageio.core.digest_spec.get_block_transform", "modulename": "bioimageio.core.digest_spec", "qualname": "get_block_transform", "kind": "function", "doc": "

returns how a model's output tensor shapes relate to its input shapes

\n", "signature": "(model: bioimageio.spec.model.v0_5.ModelDescr):", "funcdef": "def"}, "bioimageio.core.digest_spec.get_io_sample_block_metas": {"fullname": "bioimageio.core.digest_spec.get_io_sample_block_metas", "modulename": "bioimageio.core.digest_spec", "qualname": "get_io_sample_block_metas", "kind": "function", "doc": "

returns an iterable yielding meta data for corresponding input and output samples

\n", "signature": "(\tmodel: bioimageio.spec.model.v0_5.ModelDescr,\tinput_sample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tns: Mapping[Tuple[bioimageio.spec.model.v0_5.TensorId, bioimageio.spec.model.v0_5.AxisId], int],\tbatch_size: int = 1) -> Tuple[int, Iterable[bioimageio.core.digest_spec.IO_SampleBlockMeta]]:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_tensor": {"fullname": "bioimageio.core.digest_spec.get_tensor", "modulename": "bioimageio.core.digest_spec", "qualname": "get_tensor", "kind": "function", "doc": "

helper to cast/load various tensor sources

\n", "signature": "(\tsrc: Union[bioimageio.core.tensor.Tensor, xarray.core.dataarray.DataArray, numpy.ndarray[Any, numpy.dtype[Any]], pathlib.Path],\tipt: Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_5.InputTensorDescr]):", "funcdef": "def"}, "bioimageio.core.digest_spec.create_sample_for_model": {"fullname": "bioimageio.core.digest_spec.create_sample_for_model", "modulename": "bioimageio.core.digest_spec", "qualname": "create_sample_for_model", "kind": "function", "doc": "

Create a sample from a single set of input(s) for a specific bioimage.io model

\n\n

Args:\n model: a bioimage.io model description\n stat: dictionary with sample and dataset statistics (may be updated in-place!)\n inputs: the input(s) constituting a single sample.

\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)],\t*,\tstat: Optional[Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]]] = None,\tsample_id: Hashable = None,\tinputs: Optional[Mapping[bioimageio.spec.model.v0_5.TensorId, Union[bioimageio.core.tensor.Tensor, xarray.core.dataarray.DataArray, numpy.ndarray[Any, numpy.dtype[Any]], pathlib.Path]]] = None,\t**kwargs: numpy.ndarray[typing.Any, numpy.dtype[typing.Any]]) -> bioimageio.core.sample.Sample:", "funcdef": "def"}, "bioimageio.core.digest_spec.load_sample_for_model": {"fullname": "bioimageio.core.digest_spec.load_sample_for_model", "modulename": "bioimageio.core.digest_spec", "qualname": "load_sample_for_model", "kind": "function", "doc": "

load a single sample from paths that can be processed by model

\n", "signature": "(\t*,\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)],\tpaths: Mapping[bioimageio.spec.model.v0_5.TensorId, pathlib.Path],\taxes: Optional[Mapping[bioimageio.spec.model.v0_5.TensorId, Sequence[Union[bioimageio.spec.model.v0_5.AxisId, Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis]]]] = None,\tstat: Optional[Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]]] = None,\tsample_id: Optional[Hashable] = None):", "funcdef": "def"}, "bioimageio.core.io": {"fullname": "bioimageio.core.io", "modulename": "bioimageio.core.io", "kind": "module", "doc": "

\n"}, "bioimageio.core.io.load_image": {"fullname": "bioimageio.core.io.load_image", "modulename": "bioimageio.core.io", "qualname": "load_image", "kind": "function", "doc": "

load a single image as numpy array

\n\n

Args:\n path: image path\n is_volume: deprecated

\n", "signature": "(\tpath: pathlib.Path,\tis_volume: Optional[bool] = None) -> numpy.ndarray[typing.Any, numpy.dtype[typing.Any]]:", "funcdef": "def"}, "bioimageio.core.io.load_tensor": {"fullname": "bioimageio.core.io.load_tensor", "modulename": "bioimageio.core.io", "qualname": "load_tensor", "kind": "function", "doc": "

\n", "signature": "(\tpath: pathlib.Path,\taxes: Optional[Sequence[Union[bioimageio.spec.model.v0_5.AxisId, Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis]]] = None) -> bioimageio.core.tensor.Tensor:", "funcdef": "def"}, "bioimageio.core.io.save_tensor": {"fullname": "bioimageio.core.io.save_tensor", "modulename": "bioimageio.core.io", "qualname": "save_tensor", "kind": "function", "doc": "

\n", "signature": "(path: pathlib.Path, tensor: bioimageio.core.tensor.Tensor) -> None:", "funcdef": "def"}, "bioimageio.core.io.save_sample": {"fullname": "bioimageio.core.io.save_sample", "modulename": "bioimageio.core.io", "qualname": "save_sample", "kind": "function", "doc": "

save a sample to path

\n\n

If path is a pathlib.Path or a string it must contain {member_id} and may contain {sample_id},\nwhich are resolved with the sample object.

\n", "signature": "(\tpath: Union[pathlib.Path, str, Mapping[bioimageio.spec.model.v0_5.TensorId, pathlib.Path]],\tsample: bioimageio.core.sample.Sample) -> None:", "funcdef": "def"}, "bioimageio.core.io.save_dataset_stat": {"fullname": "bioimageio.core.io.save_dataset_stat", "modulename": "bioimageio.core.io", "qualname": "save_dataset_stat", "kind": "function", "doc": "

\n", "signature": "(\tstat: Mapping[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]],\tpath: pathlib.Path):", "funcdef": "def"}, "bioimageio.core.io.load_dataset_stat": {"fullname": "bioimageio.core.io.load_dataset_stat", "modulename": "bioimageio.core.io", "qualname": "load_dataset_stat", "kind": "function", "doc": "

\n", "signature": "(path: pathlib.Path):", "funcdef": "def"}, "bioimageio.core.model_adapters": {"fullname": "bioimageio.core.model_adapters", "modulename": "bioimageio.core.model_adapters", "kind": "module", "doc": "

\n"}, "bioimageio.core.prediction": {"fullname": "bioimageio.core.prediction", "modulename": "bioimageio.core.prediction", "kind": "module", "doc": "

\n"}, "bioimageio.core.prediction.predict": {"fullname": "bioimageio.core.prediction.predict", "modulename": "bioimageio.core.prediction", "qualname": "predict", "kind": "function", "doc": "

Run prediction for a single set of input(s) with a bioimage.io model

\n\n

Args:\n model: model to predict with.\n May be given as RDF source, model description or prediction pipeline.\n inputs: the input sample or the named input(s) for this model as a dictionary\n sample_id: the sample id.\n blocksize_parameter: (optional) tile the input into blocks parametrized by\n blocksize according to any parametrized axis sizes defined in the model RDF.\n Note: For a predetermined, fixed block shape use input_block_shape\n input_block_shape: (optional) tile the input sample tensors into blocks.\n Note: For a parameterized block shape, not dealing with the exact block shape,\n use blocksize_parameter.\n skip_preprocessing: flag to skip the model's preprocessing\n skip_postprocessing: flag to skip the model's postprocessing\n save_output_path: A path with {member_id} {sample_id} in it\n to save the output to.

\n", "signature": "(\t*,\tmodel: Union[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr, bioimageio.core._prediction_pipeline.PredictionPipeline],\tinputs: Union[bioimageio.core.sample.Sample, Mapping[bioimageio.spec.model.v0_5.TensorId, Union[bioimageio.core.tensor.Tensor, xarray.core.dataarray.DataArray, numpy.ndarray[Any, numpy.dtype[Any]], pathlib.Path]]],\tsample_id: Hashable = 'sample',\tblocksize_parameter: Union[int, Mapping[Tuple[bioimageio.spec.model.v0_5.TensorId, bioimageio.spec.model.v0_5.AxisId], int], NoneType] = None,\tinput_block_shape: Optional[Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]] = None,\tskip_preprocessing: bool = False,\tskip_postprocessing: bool = False,\tsave_output_path: Union[pathlib.Path, str, NoneType] = None) -> bioimageio.core.sample.Sample:", "funcdef": "def"}, "bioimageio.core.prediction.predict_many": {"fullname": "bioimageio.core.prediction.predict_many", "modulename": "bioimageio.core.prediction", "qualname": "predict_many", "kind": "function", "doc": "

Run prediction for a multiple sets of inputs with a bioimage.io model

\n\n

Args:\n model: model to predict with.\n May be given as RDF source, model description or prediction pipeline.\n inputs: An iterable of the named input(s) for this model as a dictionary.\n sample_id: the sample id.\n note: {i} will be formatted as the i-th sample.\n If {i} (or {i:) is not present and inputs is an iterable {i:03} is appended.\n blocksize_parameter: (optional) tile the input into blocks parametrized by\n blocksize according to any parametrized axis sizes defined in the model RDF\n skip_preprocessing: flag to skip the model's preprocessing\n skip_postprocessing: flag to skip the model's postprocessing\n save_output_path: A path with {member_id} {sample_id} in it\n to save the output to.

\n", "signature": "(\t*,\tmodel: Union[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr, bioimageio.core._prediction_pipeline.PredictionPipeline],\tinputs: Iterable[Mapping[bioimageio.spec.model.v0_5.TensorId, Union[bioimageio.core.tensor.Tensor, xarray.core.dataarray.DataArray, numpy.ndarray[Any, numpy.dtype[Any]], pathlib.Path]]],\tsample_id: str = 'sample{i:03}',\tblocksize_parameter: Union[int, Mapping[Tuple[bioimageio.spec.model.v0_5.TensorId, bioimageio.spec.model.v0_5.AxisId], int], NoneType] = None,\tskip_preprocessing: bool = False,\tskip_postprocessing: bool = False,\tsave_output_path: Union[pathlib.Path, str, NoneType] = None) -> Iterator[bioimageio.core.sample.Sample]:", "funcdef": "def"}, "bioimageio.core.proc_ops": {"fullname": "bioimageio.core.proc_ops", "modulename": "bioimageio.core.proc_ops", "kind": "module", "doc": "

\n"}, "bioimageio.core.proc_ops.AddKnownDatasetStats": {"fullname": "bioimageio.core.proc_ops.AddKnownDatasetStats", "modulename": "bioimageio.core.proc_ops", "qualname": "AddKnownDatasetStats", "kind": "class", "doc": "

\n", "bases": "bioimageio.core._op_base.BlockedOperator"}, "bioimageio.core.proc_ops.AddKnownDatasetStats.__init__": {"fullname": "bioimageio.core.proc_ops.AddKnownDatasetStats.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "AddKnownDatasetStats.__init__", "kind": "function", "doc": "

\n", "signature": "(\tdataset_stats: Mapping[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]])"}, "bioimageio.core.proc_ops.AddKnownDatasetStats.dataset_stats": {"fullname": "bioimageio.core.proc_ops.AddKnownDatasetStats.dataset_stats", "modulename": "bioimageio.core.proc_ops", "qualname": "AddKnownDatasetStats.dataset_stats", "kind": "variable", "doc": "

\n", "annotation": ": Mapping[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]"}, "bioimageio.core.proc_ops.AddKnownDatasetStats.required_measures": {"fullname": "bioimageio.core.proc_ops.AddKnownDatasetStats.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "AddKnownDatasetStats.required_measures", "kind": "variable", "doc": "

\n", "annotation": ": Set[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_ops.UpdateStats": {"fullname": "bioimageio.core.proc_ops.UpdateStats", "modulename": "bioimageio.core.proc_ops", "qualname": "UpdateStats", "kind": "class", "doc": "

Calculates sample and/or dataset measures

\n", "bases": "bioimageio.core._op_base.Operator"}, "bioimageio.core.proc_ops.UpdateStats.__init__": {"fullname": "bioimageio.core.proc_ops.UpdateStats.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "UpdateStats.__init__", "kind": "function", "doc": "

\n", "signature": "(\tstats_calculator: bioimageio.core.stat_calculators.StatsCalculator,\tkeep_updating_initial_dataset_stats: bool = False)"}, "bioimageio.core.proc_ops.UpdateStats.stats_calculator": {"fullname": "bioimageio.core.proc_ops.UpdateStats.stats_calculator", "modulename": "bioimageio.core.proc_ops", "qualname": "UpdateStats.stats_calculator", "kind": "variable", "doc": "

StatsCalculator to be used by this operator.

\n", "annotation": ": bioimageio.core.stat_calculators.StatsCalculator"}, "bioimageio.core.proc_ops.UpdateStats.keep_updating_initial_dataset_stats": {"fullname": "bioimageio.core.proc_ops.UpdateStats.keep_updating_initial_dataset_stats", "modulename": "bioimageio.core.proc_ops", "qualname": "UpdateStats.keep_updating_initial_dataset_stats", "kind": "variable", "doc": "

indicates if operator calls should keep updating initial dataset statistics or not;\nif the stats_calculator was not provided with any initial dataset statistics,\nthese are always updated with every new sample.

\n", "annotation": ": bool", "default_value": "False"}, "bioimageio.core.proc_ops.UpdateStats.required_measures": {"fullname": "bioimageio.core.proc_ops.UpdateStats.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "UpdateStats.required_measures", "kind": "variable", "doc": "

\n", "annotation": ": Set[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_ops.Binarize": {"fullname": "bioimageio.core.proc_ops.Binarize", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize", "kind": "class", "doc": "

'output = tensor > threshold'.

\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.Binarize.__init__": {"fullname": "bioimageio.core.proc_ops.Binarize.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize.__init__", "kind": "function", "doc": "

\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tthreshold: Union[float, Sequence[float]],\taxis: Optional[bioimageio.spec.model.v0_5.AxisId] = None)"}, "bioimageio.core.proc_ops.Binarize.threshold": {"fullname": "bioimageio.core.proc_ops.Binarize.threshold", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize.threshold", "kind": "variable", "doc": "

\n", "annotation": ": Union[float, Sequence[float]]"}, "bioimageio.core.proc_ops.Binarize.axis": {"fullname": "bioimageio.core.proc_ops.Binarize.axis", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize.axis", "kind": "variable", "doc": "

\n", "annotation": ": Optional[bioimageio.spec.model.v0_5.AxisId]", "default_value": "None"}, "bioimageio.core.proc_ops.Binarize.get_output_shape": {"fullname": "bioimageio.core.proc_ops.Binarize.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize.get_output_shape", "kind": "function", "doc": "

\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.Binarize.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.Binarize.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize.from_proc_descr", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_5.BinarizeDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.Clip": {"fullname": "bioimageio.core.proc_ops.Clip", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip", "kind": "class", "doc": "

\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.Clip.__init__": {"fullname": "bioimageio.core.proc_ops.Clip.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip.__init__", "kind": "function", "doc": "

\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tmin: Optional[float] = None,\tmax: Optional[float] = None)"}, "bioimageio.core.proc_ops.Clip.min": {"fullname": "bioimageio.core.proc_ops.Clip.min", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip.min", "kind": "variable", "doc": "

minimum value for clipping

\n", "annotation": ": Optional[float]", "default_value": "None"}, "bioimageio.core.proc_ops.Clip.max": {"fullname": "bioimageio.core.proc_ops.Clip.max", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip.max", "kind": "variable", "doc": "

maximum value for clipping

\n", "annotation": ": Optional[float]", "default_value": "None"}, "bioimageio.core.proc_ops.Clip.get_output_shape": {"fullname": "bioimageio.core.proc_ops.Clip.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip.get_output_shape", "kind": "function", "doc": "

\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.Clip.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.Clip.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip.from_proc_descr", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_5.ClipDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.EnsureDtype": {"fullname": "bioimageio.core.proc_ops.EnsureDtype", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype", "kind": "class", "doc": "

\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.EnsureDtype.__init__": {"fullname": "bioimageio.core.proc_ops.EnsureDtype.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype.__init__", "kind": "function", "doc": "

\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tdtype: Literal['bool', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64'])"}, "bioimageio.core.proc_ops.EnsureDtype.dtype": {"fullname": "bioimageio.core.proc_ops.EnsureDtype.dtype", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype.dtype", "kind": "variable", "doc": "

\n", "annotation": ": Literal['bool', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64']"}, "bioimageio.core.proc_ops.EnsureDtype.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.EnsureDtype.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype.from_proc_descr", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tdescr: bioimageio.spec.model.v0_5.EnsureDtypeDescr,\tmember_id: bioimageio.spec.model.v0_5.TensorId):", "funcdef": "def"}, "bioimageio.core.proc_ops.EnsureDtype.get_descr": {"fullname": "bioimageio.core.proc_ops.EnsureDtype.get_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype.get_descr", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.proc_ops.EnsureDtype.get_output_shape": {"fullname": "bioimageio.core.proc_ops.EnsureDtype.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype.get_output_shape", "kind": "function", "doc": "

\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleLinear": {"fullname": "bioimageio.core.proc_ops.ScaleLinear", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear", "kind": "class", "doc": "

\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.ScaleLinear.__init__": {"fullname": "bioimageio.core.proc_ops.ScaleLinear.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear.__init__", "kind": "function", "doc": "

\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tgain: Union[float, xarray.core.dataarray.DataArray] = 1.0,\toffset: Union[float, xarray.core.dataarray.DataArray] = 0.0)"}, "bioimageio.core.proc_ops.ScaleLinear.gain": {"fullname": "bioimageio.core.proc_ops.ScaleLinear.gain", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear.gain", "kind": "variable", "doc": "

multiplicative factor

\n", "annotation": ": Union[float, xarray.core.dataarray.DataArray]", "default_value": "1.0"}, "bioimageio.core.proc_ops.ScaleLinear.offset": {"fullname": "bioimageio.core.proc_ops.ScaleLinear.offset", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear.offset", "kind": "variable", "doc": "

additive term

\n", "annotation": ": Union[float, xarray.core.dataarray.DataArray]", "default_value": "0.0"}, "bioimageio.core.proc_ops.ScaleLinear.get_output_shape": {"fullname": "bioimageio.core.proc_ops.ScaleLinear.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear.get_output_shape", "kind": "function", "doc": "

\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleLinear.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.ScaleLinear.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear.from_proc_descr", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleMeanVariance": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance", "kind": "class", "doc": "

\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.ScaleMeanVariance.__init__": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.__init__", "kind": "function", "doc": "

\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]] = None,\treference_tensor: Optional[bioimageio.spec.model.v0_5.TensorId] = None,\teps: float = 1e-06)"}, "bioimageio.core.proc_ops.ScaleMeanVariance.axes": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.axes", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.axes", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]]", "default_value": "None"}, "bioimageio.core.proc_ops.ScaleMeanVariance.reference_tensor": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.reference_tensor", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.reference_tensor", "kind": "variable", "doc": "

\n", "annotation": ": Optional[bioimageio.spec.model.v0_5.TensorId]", "default_value": "None"}, "bioimageio.core.proc_ops.ScaleMeanVariance.eps": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.eps", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.eps", "kind": "variable", "doc": "

\n", "annotation": ": float", "default_value": "1e-06"}, "bioimageio.core.proc_ops.ScaleMeanVariance.mean": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.mean", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.mean", "kind": "variable", "doc": "

\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean]"}, "bioimageio.core.proc_ops.ScaleMeanVariance.std": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.std", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.std", "kind": "variable", "doc": "

\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd]"}, "bioimageio.core.proc_ops.ScaleMeanVariance.ref_mean": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.ref_mean", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.ref_mean", "kind": "variable", "doc": "

\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean]"}, "bioimageio.core.proc_ops.ScaleMeanVariance.ref_std": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.ref_std", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.ref_std", "kind": "variable", "doc": "

\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd]"}, "bioimageio.core.proc_ops.ScaleMeanVariance.required_measures": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.required_measures", "kind": "variable", "doc": "

\n"}, "bioimageio.core.proc_ops.ScaleMeanVariance.get_output_shape": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.get_output_shape", "kind": "function", "doc": "

\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleMeanVariance.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.from_proc_descr", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr, bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleRange": {"fullname": "bioimageio.core.proc_ops.ScaleRange", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange", "kind": "class", "doc": "

\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.ScaleRange.__init__": {"fullname": "bioimageio.core.proc_ops.ScaleRange.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.__init__", "kind": "function", "doc": "

\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tlower_percentile: dataclasses.InitVar[typing.Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile, NoneType]] = None,\tupper_percentile: dataclasses.InitVar[typing.Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile, NoneType]] = None,\teps: float = 1e-06)"}, "bioimageio.core.proc_ops.ScaleRange.lower_percentile": {"fullname": "bioimageio.core.proc_ops.ScaleRange.lower_percentile", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.lower_percentile", "kind": "variable", "doc": "

\n", "annotation": ": dataclasses.InitVar[typing.Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile, NoneType]]", "default_value": "None"}, "bioimageio.core.proc_ops.ScaleRange.upper_percentile": {"fullname": "bioimageio.core.proc_ops.ScaleRange.upper_percentile", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.upper_percentile", "kind": "variable", "doc": "

\n", "annotation": ": dataclasses.InitVar[typing.Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile, NoneType]]", "default_value": "None"}, "bioimageio.core.proc_ops.ScaleRange.lower": {"fullname": "bioimageio.core.proc_ops.ScaleRange.lower", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.lower", "kind": "variable", "doc": "

\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile]"}, "bioimageio.core.proc_ops.ScaleRange.upper": {"fullname": "bioimageio.core.proc_ops.ScaleRange.upper", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.upper", "kind": "variable", "doc": "

\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile]"}, "bioimageio.core.proc_ops.ScaleRange.eps": {"fullname": "bioimageio.core.proc_ops.ScaleRange.eps", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.eps", "kind": "variable", "doc": "

\n", "annotation": ": float", "default_value": "1e-06"}, "bioimageio.core.proc_ops.ScaleRange.required_measures": {"fullname": "bioimageio.core.proc_ops.ScaleRange.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.required_measures", "kind": "variable", "doc": "

\n"}, "bioimageio.core.proc_ops.ScaleRange.get_output_shape": {"fullname": "bioimageio.core.proc_ops.ScaleRange.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.get_output_shape", "kind": "function", "doc": "

\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleRange.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.ScaleRange.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.from_proc_descr", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.ScaleRangeDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId):", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleRange.get_descr": {"fullname": "bioimageio.core.proc_ops.ScaleRange.get_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.get_descr", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.proc_ops.Sigmoid": {"fullname": "bioimageio.core.proc_ops.Sigmoid", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid", "kind": "class", "doc": "

1 / (1 + e^(-input)).

\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.Sigmoid.__init__": {"fullname": "bioimageio.core.proc_ops.Sigmoid.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid.__init__", "kind": "function", "doc": "

\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId)"}, "bioimageio.core.proc_ops.Sigmoid.required_measures": {"fullname": "bioimageio.core.proc_ops.Sigmoid.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid.required_measures", "kind": "variable", "doc": "

\n", "annotation": ": Collection[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_ops.Sigmoid.get_output_shape": {"fullname": "bioimageio.core.proc_ops.Sigmoid.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid.get_output_shape", "kind": "function", "doc": "

\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.Sigmoid.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.Sigmoid.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid.from_proc_descr", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_5.SigmoidDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.Sigmoid.get_descr": {"fullname": "bioimageio.core.proc_ops.Sigmoid.get_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid.get_descr", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance", "kind": "class", "doc": "

normalize to zero mean, unit variance.

\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.__init__": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.__init__", "kind": "function", "doc": "

\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tmean: Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean],\tstd: Union[bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd],\teps: float = 1e-06)"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.mean": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.mean", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.mean", "kind": "variable", "doc": "

\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean]"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.std": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.std", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.std", "kind": "variable", "doc": "

\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd]"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.eps": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.eps", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.eps", "kind": "variable", "doc": "

\n", "annotation": ": float", "default_value": "1e-06"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.required_measures": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.required_measures", "kind": "variable", "doc": "

\n", "annotation": ": Set[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd]]"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.get_output_shape": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.get_output_shape", "kind": "function", "doc": "

\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.from_proc_descr", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId):", "funcdef": "def"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.get_descr": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.get_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.get_descr", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance", "kind": "class", "doc": "

normalize to zero mean, unit variance with precomputed values.

\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.__init__": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.__init__", "kind": "function", "doc": "

\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tmean: Union[float, xarray.core.dataarray.DataArray],\tstd: Union[float, xarray.core.dataarray.DataArray],\teps: float = 1e-06)"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.mean": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.mean", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.mean", "kind": "variable", "doc": "

\n", "annotation": ": Union[float, xarray.core.dataarray.DataArray]"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.std": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.std", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.std", "kind": "variable", "doc": "

\n", "annotation": ": Union[float, xarray.core.dataarray.DataArray]"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.eps": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.eps", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.eps", "kind": "variable", "doc": "

\n", "annotation": ": float", "default_value": "1e-06"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.get_output_shape": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.get_output_shape", "kind": "function", "doc": "

\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.from_proc_descr", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tdescr: bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr,\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.get_descr": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.get_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.get_descr", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.proc_ops.ProcDescr": {"fullname": "bioimageio.core.proc_ops.ProcDescr", "modulename": "bioimageio.core.proc_ops", "qualname": "ProcDescr", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[typing.Annotated[typing.Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr, bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr], Discriminator(discriminator='id', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr, bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr], Discriminator(discriminator='id', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_ops.Processing": {"fullname": "bioimageio.core.proc_ops.Processing", "modulename": "bioimageio.core.proc_ops", "qualname": "Processing", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bioimageio.core.proc_ops.AddKnownDatasetStats, bioimageio.core.proc_ops.Binarize, bioimageio.core.proc_ops.Clip, bioimageio.core.proc_ops.EnsureDtype, bioimageio.core.proc_ops.FixedZeroMeanUnitVariance, bioimageio.core.proc_ops.ScaleLinear, bioimageio.core.proc_ops.ScaleMeanVariance, bioimageio.core.proc_ops.ScaleRange, bioimageio.core.proc_ops.Sigmoid, bioimageio.core.proc_ops.UpdateStats, bioimageio.core.proc_ops.ZeroMeanUnitVariance]"}, "bioimageio.core.proc_ops.get_proc_class": {"fullname": "bioimageio.core.proc_ops.get_proc_class", "modulename": "bioimageio.core.proc_ops", "qualname": "get_proc_class", "kind": "function", "doc": "

\n", "signature": "(\tproc_spec: Union[Annotated[Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr, bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr], Discriminator(discriminator='id', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr, bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr], Discriminator(discriminator='id', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]):", "funcdef": "def"}, "bioimageio.core.proc_setup": {"fullname": "bioimageio.core.proc_setup", "modulename": "bioimageio.core.proc_setup", "kind": "module", "doc": "

\n"}, "bioimageio.core.proc_setup.TensorDescr": {"fullname": "bioimageio.core.proc_setup.TensorDescr", "modulename": "bioimageio.core.proc_setup", "qualname": "TensorDescr", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_4.OutputTensorDescr, bioimageio.spec.model.v0_5.InputTensorDescr, bioimageio.spec.model.v0_5.OutputTensorDescr]"}, "bioimageio.core.proc_setup.PreAndPostprocessing": {"fullname": "bioimageio.core.proc_setup.PreAndPostprocessing", "modulename": "bioimageio.core.proc_setup", "qualname": "PreAndPostprocessing", "kind": "class", "doc": "

PreAndPostprocessing(pre, post)

\n", "bases": "typing.NamedTuple"}, "bioimageio.core.proc_setup.PreAndPostprocessing.__init__": {"fullname": "bioimageio.core.proc_setup.PreAndPostprocessing.__init__", "modulename": "bioimageio.core.proc_setup", "qualname": "PreAndPostprocessing.__init__", "kind": "function", "doc": "

Create new instance of PreAndPostprocessing(pre, post)

\n", "signature": "(\tpre: List[Union[bioimageio.core.proc_ops.AddKnownDatasetStats, bioimageio.core.proc_ops.Binarize, bioimageio.core.proc_ops.Clip, bioimageio.core.proc_ops.EnsureDtype, bioimageio.core.proc_ops.FixedZeroMeanUnitVariance, bioimageio.core.proc_ops.ScaleLinear, bioimageio.core.proc_ops.ScaleMeanVariance, bioimageio.core.proc_ops.ScaleRange, bioimageio.core.proc_ops.Sigmoid, bioimageio.core.proc_ops.UpdateStats, bioimageio.core.proc_ops.ZeroMeanUnitVariance]],\tpost: List[Union[bioimageio.core.proc_ops.AddKnownDatasetStats, bioimageio.core.proc_ops.Binarize, bioimageio.core.proc_ops.Clip, bioimageio.core.proc_ops.EnsureDtype, bioimageio.core.proc_ops.FixedZeroMeanUnitVariance, bioimageio.core.proc_ops.ScaleLinear, bioimageio.core.proc_ops.ScaleMeanVariance, bioimageio.core.proc_ops.ScaleRange, bioimageio.core.proc_ops.Sigmoid, bioimageio.core.proc_ops.UpdateStats, bioimageio.core.proc_ops.ZeroMeanUnitVariance]])"}, "bioimageio.core.proc_setup.PreAndPostprocessing.pre": {"fullname": "bioimageio.core.proc_setup.PreAndPostprocessing.pre", "modulename": "bioimageio.core.proc_setup", "qualname": "PreAndPostprocessing.pre", "kind": "variable", "doc": "

Alias for field number 0

\n", "annotation": ": List[Union[bioimageio.core.proc_ops.AddKnownDatasetStats, bioimageio.core.proc_ops.Binarize, bioimageio.core.proc_ops.Clip, bioimageio.core.proc_ops.EnsureDtype, bioimageio.core.proc_ops.FixedZeroMeanUnitVariance, bioimageio.core.proc_ops.ScaleLinear, bioimageio.core.proc_ops.ScaleMeanVariance, bioimageio.core.proc_ops.ScaleRange, bioimageio.core.proc_ops.Sigmoid, bioimageio.core.proc_ops.UpdateStats, bioimageio.core.proc_ops.ZeroMeanUnitVariance]]"}, "bioimageio.core.proc_setup.PreAndPostprocessing.post": {"fullname": "bioimageio.core.proc_setup.PreAndPostprocessing.post", "modulename": "bioimageio.core.proc_setup", "qualname": "PreAndPostprocessing.post", "kind": "variable", "doc": "

Alias for field number 1

\n", "annotation": ": List[Union[bioimageio.core.proc_ops.AddKnownDatasetStats, bioimageio.core.proc_ops.Binarize, bioimageio.core.proc_ops.Clip, bioimageio.core.proc_ops.EnsureDtype, bioimageio.core.proc_ops.FixedZeroMeanUnitVariance, bioimageio.core.proc_ops.ScaleLinear, bioimageio.core.proc_ops.ScaleMeanVariance, bioimageio.core.proc_ops.ScaleRange, bioimageio.core.proc_ops.Sigmoid, bioimageio.core.proc_ops.UpdateStats, bioimageio.core.proc_ops.ZeroMeanUnitVariance]]"}, "bioimageio.core.proc_setup.setup_pre_and_postprocessing": {"fullname": "bioimageio.core.proc_setup.setup_pre_and_postprocessing", "modulename": "bioimageio.core.proc_setup", "qualname": "setup_pre_and_postprocessing", "kind": "function", "doc": "

Get pre- and postprocessing operators for a model description.\nuserd in `bioimageio.core.create_prediction_pipeline

\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)],\tdataset_for_initial_statistics: Iterable[bioimageio.core.sample.Sample],\tkeep_updating_initial_dataset_stats: bool = False,\tfixed_dataset_stats: Optional[Mapping[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]]] = None) -> bioimageio.core.proc_setup.PreAndPostprocessing:", "funcdef": "def"}, "bioimageio.core.proc_setup.RequiredMeasures": {"fullname": "bioimageio.core.proc_setup.RequiredMeasures", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredMeasures", "kind": "class", "doc": "

RequiredMeasures(pre, post)

\n", "bases": "typing.NamedTuple"}, "bioimageio.core.proc_setup.RequiredMeasures.__init__": {"fullname": "bioimageio.core.proc_setup.RequiredMeasures.__init__", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredMeasures.__init__", "kind": "function", "doc": "

Create new instance of RequiredMeasures(pre, post)

\n", "signature": "(\tpre: Set[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]],\tpost: Set[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]])"}, "bioimageio.core.proc_setup.RequiredMeasures.pre": {"fullname": "bioimageio.core.proc_setup.RequiredMeasures.pre", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredMeasures.pre", "kind": "variable", "doc": "

Alias for field number 0

\n", "annotation": ": Set[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_setup.RequiredMeasures.post": {"fullname": "bioimageio.core.proc_setup.RequiredMeasures.post", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredMeasures.post", "kind": "variable", "doc": "

Alias for field number 1

\n", "annotation": ": Set[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_setup.RequiredDatasetMeasures": {"fullname": "bioimageio.core.proc_setup.RequiredDatasetMeasures", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredDatasetMeasures", "kind": "class", "doc": "

RequiredDatasetMeasures(pre, post)

\n", "bases": "typing.NamedTuple"}, "bioimageio.core.proc_setup.RequiredDatasetMeasures.__init__": {"fullname": "bioimageio.core.proc_setup.RequiredDatasetMeasures.__init__", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredDatasetMeasures.__init__", "kind": "function", "doc": "

Create new instance of RequiredDatasetMeasures(pre, post)

\n", "signature": "(\tpre: Set[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]],\tpost: Set[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]])"}, "bioimageio.core.proc_setup.RequiredDatasetMeasures.pre": {"fullname": "bioimageio.core.proc_setup.RequiredDatasetMeasures.pre", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredDatasetMeasures.pre", "kind": "variable", "doc": "

Alias for field number 0

\n", "annotation": ": Set[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_setup.RequiredDatasetMeasures.post": {"fullname": "bioimageio.core.proc_setup.RequiredDatasetMeasures.post", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredDatasetMeasures.post", "kind": "variable", "doc": "

Alias for field number 1

\n", "annotation": ": Set[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_setup.RequiredSampleMeasures": {"fullname": "bioimageio.core.proc_setup.RequiredSampleMeasures", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredSampleMeasures", "kind": "class", "doc": "

RequiredSampleMeasures(pre, post)

\n", "bases": "typing.NamedTuple"}, "bioimageio.core.proc_setup.RequiredSampleMeasures.__init__": {"fullname": "bioimageio.core.proc_setup.RequiredSampleMeasures.__init__", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredSampleMeasures.__init__", "kind": "function", "doc": "

Create new instance of RequiredSampleMeasures(pre, post)

\n", "signature": "(\tpre: Set[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]],\tpost: Set[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]])"}, "bioimageio.core.proc_setup.RequiredSampleMeasures.pre": {"fullname": "bioimageio.core.proc_setup.RequiredSampleMeasures.pre", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredSampleMeasures.pre", "kind": "variable", "doc": "

Alias for field number 0

\n", "annotation": ": Set[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_setup.RequiredSampleMeasures.post": {"fullname": "bioimageio.core.proc_setup.RequiredSampleMeasures.post", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredSampleMeasures.post", "kind": "variable", "doc": "

Alias for field number 1

\n", "annotation": ": Set[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_setup.get_requried_measures": {"fullname": "bioimageio.core.proc_setup.get_requried_measures", "modulename": "bioimageio.core.proc_setup", "qualname": "get_requried_measures", "kind": "function", "doc": "

\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]) -> bioimageio.core.proc_setup.RequiredMeasures:", "funcdef": "def"}, "bioimageio.core.proc_setup.get_required_dataset_measures": {"fullname": "bioimageio.core.proc_setup.get_required_dataset_measures", "modulename": "bioimageio.core.proc_setup", "qualname": "get_required_dataset_measures", "kind": "function", "doc": "

\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]) -> bioimageio.core.proc_setup.RequiredDatasetMeasures:", "funcdef": "def"}, "bioimageio.core.proc_setup.get_requried_sample_measures": {"fullname": "bioimageio.core.proc_setup.get_requried_sample_measures", "modulename": "bioimageio.core.proc_setup", "qualname": "get_requried_sample_measures", "kind": "function", "doc": "

\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]) -> bioimageio.core.proc_setup.RequiredSampleMeasures:", "funcdef": "def"}, "bioimageio.core.sample": {"fullname": "bioimageio.core.sample", "modulename": "bioimageio.core.sample", "kind": "module", "doc": "

\n"}, "bioimageio.core.sample.Sample": {"fullname": "bioimageio.core.sample.Sample", "modulename": "bioimageio.core.sample", "qualname": "Sample", "kind": "class", "doc": "

A dataset sample

\n"}, "bioimageio.core.sample.Sample.__init__": {"fullname": "bioimageio.core.sample.Sample.__init__", "modulename": "bioimageio.core.sample", "qualname": "Sample.__init__", "kind": "function", "doc": "

\n", "signature": "(\tmembers: Dict[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.tensor.Tensor],\tstat: Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]],\tid: Hashable)"}, "bioimageio.core.sample.Sample.members": {"fullname": "bioimageio.core.sample.Sample.members", "modulename": "bioimageio.core.sample", "qualname": "Sample.members", "kind": "variable", "doc": "

the sample's tensors

\n", "annotation": ": Dict[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.tensor.Tensor]"}, "bioimageio.core.sample.Sample.stat": {"fullname": "bioimageio.core.sample.Sample.stat", "modulename": "bioimageio.core.sample", "qualname": "Sample.stat", "kind": "variable", "doc": "

sample and dataset statistics

\n", "annotation": ": Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]"}, "bioimageio.core.sample.Sample.id": {"fullname": "bioimageio.core.sample.Sample.id", "modulename": "bioimageio.core.sample", "qualname": "Sample.id", "kind": "variable", "doc": "

identifier within the sample's dataset

\n", "annotation": ": Hashable"}, "bioimageio.core.sample.Sample.shape": {"fullname": "bioimageio.core.sample.Sample.shape", "modulename": "bioimageio.core.sample", "qualname": "Sample.shape", "kind": "variable", "doc": "

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]"}, "bioimageio.core.sample.Sample.split_into_blocks": {"fullname": "bioimageio.core.sample.Sample.split_into_blocks", "modulename": "bioimageio.core.sample", "qualname": "Sample.split_into_blocks", "kind": "function", "doc": "

\n", "signature": "(\tself,\tblock_shapes: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\thalo: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, Union[int, Tuple[int, int], bioimageio.core.common.Halo]]],\tpad_mode: Literal['edge', 'reflect', 'symmetric'],\tbroadcast: bool = False) -> Tuple[int, Iterable[bioimageio.core.sample.SampleBlockWithOrigin]]:", "funcdef": "def"}, "bioimageio.core.sample.Sample.as_single_block": {"fullname": "bioimageio.core.sample.Sample.as_single_block", "modulename": "bioimageio.core.sample", "qualname": "Sample.as_single_block", "kind": "function", "doc": "

\n", "signature": "(\tself,\thalo: Optional[Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.Halo]]] = None):", "funcdef": "def"}, "bioimageio.core.sample.Sample.from_blocks": {"fullname": "bioimageio.core.sample.Sample.from_blocks", "modulename": "bioimageio.core.sample", "qualname": "Sample.from_blocks", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tsample_blocks: Iterable[bioimageio.core.sample.SampleBlock],\t*,\tfill_value: float = nan) -> Self:", "funcdef": "def"}, "bioimageio.core.sample.SampleBlockBase": {"fullname": "bioimageio.core.sample.SampleBlockBase", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase", "kind": "class", "doc": "

base class for SampleBlockMeta and SampleBlock

\n", "bases": "typing.Generic[~BlockT]"}, "bioimageio.core.sample.SampleBlockBase.__init__": {"fullname": "bioimageio.core.sample.SampleBlockBase.__init__", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.__init__", "kind": "function", "doc": "

\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tsample_id: Hashable,\tblocks: Dict[bioimageio.spec.model.v0_5.TensorId, ~BlockT],\tblock_index: int,\tblocks_in_sample: int)"}, "bioimageio.core.sample.SampleBlockBase.sample_shape": {"fullname": "bioimageio.core.sample.SampleBlockBase.sample_shape", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.sample_shape", "kind": "variable", "doc": "

the sample shape this block represents a part of

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]"}, "bioimageio.core.sample.SampleBlockBase.sample_id": {"fullname": "bioimageio.core.sample.SampleBlockBase.sample_id", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.sample_id", "kind": "variable", "doc": "

identifier for the sample within its dataset

\n", "annotation": ": Hashable"}, "bioimageio.core.sample.SampleBlockBase.blocks": {"fullname": "bioimageio.core.sample.SampleBlockBase.blocks", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.blocks", "kind": "variable", "doc": "

Individual tensor blocks comprising this sample block

\n", "annotation": ": Dict[bioimageio.spec.model.v0_5.TensorId, ~BlockT]"}, "bioimageio.core.sample.SampleBlockBase.block_index": {"fullname": "bioimageio.core.sample.SampleBlockBase.block_index", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.block_index", "kind": "variable", "doc": "

the n-th block of the sample

\n", "annotation": ": int"}, "bioimageio.core.sample.SampleBlockBase.blocks_in_sample": {"fullname": "bioimageio.core.sample.SampleBlockBase.blocks_in_sample", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.blocks_in_sample", "kind": "variable", "doc": "

total number of blocks in the sample

\n", "annotation": ": int"}, "bioimageio.core.sample.SampleBlockBase.shape": {"fullname": "bioimageio.core.sample.SampleBlockBase.shape", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.shape", "kind": "variable", "doc": "

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]"}, "bioimageio.core.sample.SampleBlockBase.inner_shape": {"fullname": "bioimageio.core.sample.SampleBlockBase.inner_shape", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.inner_shape", "kind": "variable", "doc": "

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]"}, "bioimageio.core.sample.LinearSampleAxisTransform": {"fullname": "bioimageio.core.sample.LinearSampleAxisTransform", "modulename": "bioimageio.core.sample", "qualname": "LinearSampleAxisTransform", "kind": "class", "doc": "

\n", "bases": "bioimageio.core.block_meta.LinearAxisTransform"}, "bioimageio.core.sample.LinearSampleAxisTransform.__init__": {"fullname": "bioimageio.core.sample.LinearSampleAxisTransform.__init__", "modulename": "bioimageio.core.sample", "qualname": "LinearSampleAxisTransform.__init__", "kind": "function", "doc": "

\n", "signature": "(\taxis: bioimageio.spec.model.v0_5.AxisId,\tscale: float,\toffset: int,\tmember: bioimageio.spec.model.v0_5.TensorId)"}, "bioimageio.core.sample.LinearSampleAxisTransform.member": {"fullname": "bioimageio.core.sample.LinearSampleAxisTransform.member", "modulename": "bioimageio.core.sample", "qualname": "LinearSampleAxisTransform.member", "kind": "variable", "doc": "

\n", "annotation": ": bioimageio.spec.model.v0_5.TensorId"}, "bioimageio.core.sample.SampleBlockMeta": {"fullname": "bioimageio.core.sample.SampleBlockMeta", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockMeta", "kind": "class", "doc": "

Meta data of a dataset sample block

\n", "bases": "bioimageio.core.sample.SampleBlockBase[bioimageio.core.block_meta.BlockMeta]"}, "bioimageio.core.sample.SampleBlockMeta.__init__": {"fullname": "bioimageio.core.sample.SampleBlockMeta.__init__", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockMeta.__init__", "kind": "function", "doc": "

\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tsample_id: Hashable,\tblocks: Dict[bioimageio.spec.model.v0_5.TensorId, ~BlockT],\tblock_index: int,\tblocks_in_sample: int)"}, "bioimageio.core.sample.SampleBlockMeta.get_transformed": {"fullname": "bioimageio.core.sample.SampleBlockMeta.get_transformed", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockMeta.get_transformed", "kind": "function", "doc": "

\n", "signature": "(\tself,\tnew_axes: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, Union[bioimageio.core.sample.LinearSampleAxisTransform, int]]]) -> Self:", "funcdef": "def"}, "bioimageio.core.sample.SampleBlockMeta.with_data": {"fullname": "bioimageio.core.sample.SampleBlockMeta.with_data", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockMeta.with_data", "kind": "function", "doc": "

\n", "signature": "(\tself,\tdata: Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.tensor.Tensor],\t*,\tstat: Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]]) -> bioimageio.core.sample.SampleBlock:", "funcdef": "def"}, "bioimageio.core.sample.SampleBlock": {"fullname": "bioimageio.core.sample.SampleBlock", "modulename": "bioimageio.core.sample", "qualname": "SampleBlock", "kind": "class", "doc": "

A block of a dataset sample

\n", "bases": "bioimageio.core.sample.SampleBlockBase[bioimageio.core.block.Block]"}, "bioimageio.core.sample.SampleBlock.__init__": {"fullname": "bioimageio.core.sample.SampleBlock.__init__", "modulename": "bioimageio.core.sample", "qualname": "SampleBlock.__init__", "kind": "function", "doc": "

\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tsample_id: Hashable,\tblocks: Dict[bioimageio.spec.model.v0_5.TensorId, ~BlockT],\tblock_index: int,\tblocks_in_sample: int,\tstat: Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]])"}, "bioimageio.core.sample.SampleBlock.stat": {"fullname": "bioimageio.core.sample.SampleBlock.stat", "modulename": "bioimageio.core.sample", "qualname": "SampleBlock.stat", "kind": "variable", "doc": "

computed statistics

\n", "annotation": ": Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]"}, "bioimageio.core.sample.SampleBlock.members": {"fullname": "bioimageio.core.sample.SampleBlock.members", "modulename": "bioimageio.core.sample", "qualname": "SampleBlock.members", "kind": "variable", "doc": "

the sample block's tensors

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.tensor.Tensor]"}, "bioimageio.core.sample.SampleBlock.get_transformed_meta": {"fullname": "bioimageio.core.sample.SampleBlock.get_transformed_meta", "modulename": "bioimageio.core.sample", "qualname": "SampleBlock.get_transformed_meta", "kind": "function", "doc": "

\n", "signature": "(\tself,\tnew_axes: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, Union[bioimageio.core.sample.LinearSampleAxisTransform, int]]]) -> bioimageio.core.sample.SampleBlockMeta:", "funcdef": "def"}, "bioimageio.core.sample.SampleBlockWithOrigin": {"fullname": "bioimageio.core.sample.SampleBlockWithOrigin", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockWithOrigin", "kind": "class", "doc": "

\n", "bases": "bioimageio.core.sample.SampleBlockBase[bioimageio.core.block.Block]"}, "bioimageio.core.sample.SampleBlockWithOrigin.__init__": {"fullname": "bioimageio.core.sample.SampleBlockWithOrigin.__init__", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockWithOrigin.__init__", "kind": "function", "doc": "

\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tsample_id: Hashable,\tblocks: Dict[bioimageio.spec.model.v0_5.TensorId, ~BlockT],\tblock_index: int,\tblocks_in_sample: int,\tstat: Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]],\torigin: bioimageio.core.sample.Sample)"}, "bioimageio.core.sample.SampleBlockWithOrigin.origin": {"fullname": "bioimageio.core.sample.SampleBlockWithOrigin.origin", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockWithOrigin.origin", "kind": "variable", "doc": "

the sample this sample black was taken from

\n", "annotation": ": bioimageio.core.sample.Sample"}, "bioimageio.core.sample.sample_block_meta_generator": {"fullname": "bioimageio.core.sample.sample_block_meta_generator", "modulename": "bioimageio.core.sample", "qualname": "sample_block_meta_generator", "kind": "function", "doc": "

\n", "signature": "(\tblocks: Iterable[Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.block_meta.BlockMeta]],\t*,\tsample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tsample_id: Hashable):", "funcdef": "def"}, "bioimageio.core.sample.sample_block_generator": {"fullname": "bioimageio.core.sample.sample_block_generator", "modulename": "bioimageio.core.sample", "qualname": "sample_block_generator", "kind": "function", "doc": "

\n", "signature": "(\tblocks: Iterable[Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.block_meta.BlockMeta]],\t*,\torigin: bioimageio.core.sample.Sample,\tpad_mode: Literal['edge', 'reflect', 'symmetric']):", "funcdef": "def"}, "bioimageio.core.stat_calculators": {"fullname": "bioimageio.core.stat_calculators", "modulename": "bioimageio.core.stat_calculators", "kind": "module", "doc": "

\n"}, "bioimageio.core.stat_calculators.MeanCalculator": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator", "kind": "class", "doc": "

to calculate sample and dataset mean for in-memory samples

\n"}, "bioimageio.core.stat_calculators.MeanCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]])"}, "bioimageio.core.stat_calculators.MeanCalculator.compute": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator.compute", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator.compute", "kind": "function", "doc": "

\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[bioimageio.core.stat_measures.SampleMean, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanCalculator.update": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator.update", "kind": "function", "doc": "

\n", "signature": "(self, sample: bioimageio.core.sample.Sample) -> None:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanCalculator.compute_and_update": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator.compute_and_update", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator.compute_and_update", "kind": "function", "doc": "

\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[bioimageio.core.stat_measures.SampleMean, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanCalculator.finalize": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator.finalize", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator.finalize", "kind": "function", "doc": "

\n", "signature": "(\tself) -> Dict[bioimageio.core.stat_measures.DatasetMean, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanVarStdCalculator": {"fullname": "bioimageio.core.stat_calculators.MeanVarStdCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanVarStdCalculator", "kind": "class", "doc": "

to calculate sample and dataset mean, variance or standard deviation

\n"}, "bioimageio.core.stat_calculators.MeanVarStdCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.MeanVarStdCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanVarStdCalculator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]])"}, "bioimageio.core.stat_calculators.MeanVarStdCalculator.compute": {"fullname": "bioimageio.core.stat_calculators.MeanVarStdCalculator.compute", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanVarStdCalculator.compute", "kind": "function", "doc": "

\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleStd], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanVarStdCalculator.update": {"fullname": "bioimageio.core.stat_calculators.MeanVarStdCalculator.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanVarStdCalculator.update", "kind": "function", "doc": "

\n", "signature": "(self, sample: bioimageio.core.sample.Sample):", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanVarStdCalculator.finalize": {"fullname": "bioimageio.core.stat_calculators.MeanVarStdCalculator.finalize", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanVarStdCalculator.finalize", "kind": "function", "doc": "

\n", "signature": "(\tself) -> Dict[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetStd], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.SamplePercentilesCalculator": {"fullname": "bioimageio.core.stat_calculators.SamplePercentilesCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "SamplePercentilesCalculator", "kind": "class", "doc": "

to calculate sample percentiles

\n"}, "bioimageio.core.stat_calculators.SamplePercentilesCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.SamplePercentilesCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "SamplePercentilesCalculator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]],\tqs: Collection[float])"}, "bioimageio.core.stat_calculators.SamplePercentilesCalculator.compute": {"fullname": "bioimageio.core.stat_calculators.SamplePercentilesCalculator.compute", "modulename": "bioimageio.core.stat_calculators", "qualname": "SamplePercentilesCalculator.compute", "kind": "function", "doc": "

\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[bioimageio.core.stat_measures.SampleQuantile, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanPercentilesCalculator": {"fullname": "bioimageio.core.stat_calculators.MeanPercentilesCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanPercentilesCalculator", "kind": "class", "doc": "

to calculate dataset percentiles heuristically by averaging across samples\nnote: the returned dataset percentiles are an estiamte and not mathematically correct

\n"}, "bioimageio.core.stat_calculators.MeanPercentilesCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.MeanPercentilesCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanPercentilesCalculator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]],\tqs: Collection[float])"}, "bioimageio.core.stat_calculators.MeanPercentilesCalculator.update": {"fullname": "bioimageio.core.stat_calculators.MeanPercentilesCalculator.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanPercentilesCalculator.update", "kind": "function", "doc": "

\n", "signature": "(self, sample: bioimageio.core.sample.Sample):", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanPercentilesCalculator.finalize": {"fullname": "bioimageio.core.stat_calculators.MeanPercentilesCalculator.finalize", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanPercentilesCalculator.finalize", "kind": "function", "doc": "

\n", "signature": "(\tself) -> Dict[bioimageio.core.stat_measures.DatasetPercentile, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.CrickPercentilesCalculator": {"fullname": "bioimageio.core.stat_calculators.CrickPercentilesCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "CrickPercentilesCalculator", "kind": "class", "doc": "

to calculate dataset percentiles with the experimental crick libray

\n"}, "bioimageio.core.stat_calculators.CrickPercentilesCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.CrickPercentilesCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "CrickPercentilesCalculator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]],\tqs: Collection[float])"}, "bioimageio.core.stat_calculators.CrickPercentilesCalculator.update": {"fullname": "bioimageio.core.stat_calculators.CrickPercentilesCalculator.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "CrickPercentilesCalculator.update", "kind": "function", "doc": "

\n", "signature": "(self, part: bioimageio.core.sample.Sample):", "funcdef": "def"}, "bioimageio.core.stat_calculators.CrickPercentilesCalculator.finalize": {"fullname": "bioimageio.core.stat_calculators.CrickPercentilesCalculator.finalize", "modulename": "bioimageio.core.stat_calculators", "qualname": "CrickPercentilesCalculator.finalize", "kind": "function", "doc": "

\n", "signature": "(\tself) -> Dict[bioimageio.core.stat_measures.DatasetPercentile, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator": {"fullname": "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "NaiveSampleMeasureCalculator", "kind": "class", "doc": "

wrapper for measures to match interface of other sample measure calculators

\n"}, "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "NaiveSampleMeasureCalculator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\tmeasure: Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)])"}, "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.tensor_name": {"fullname": "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.tensor_name", "modulename": "bioimageio.core.stat_calculators", "qualname": "NaiveSampleMeasureCalculator.tensor_name", "kind": "variable", "doc": "

\n"}, "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.measure": {"fullname": "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.measure", "modulename": "bioimageio.core.stat_calculators", "qualname": "NaiveSampleMeasureCalculator.measure", "kind": "variable", "doc": "

\n"}, "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.compute": {"fullname": "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.compute", "modulename": "bioimageio.core.stat_calculators", "qualname": "NaiveSampleMeasureCalculator.compute", "kind": "function", "doc": "

\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.SampleMeasureCalculator": {"fullname": "bioimageio.core.stat_calculators.SampleMeasureCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "SampleMeasureCalculator", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bioimageio.core.stat_calculators.MeanCalculator, bioimageio.core.stat_calculators.MeanVarStdCalculator, bioimageio.core.stat_calculators.SamplePercentilesCalculator, bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator]"}, "bioimageio.core.stat_calculators.DatasetMeasureCalculator": {"fullname": "bioimageio.core.stat_calculators.DatasetMeasureCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "DatasetMeasureCalculator", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bioimageio.core.stat_calculators.MeanCalculator, bioimageio.core.stat_calculators.MeanVarStdCalculator, bioimageio.core.stat_calculators.MeanPercentilesCalculator]"}, "bioimageio.core.stat_calculators.StatsCalculator": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator", "kind": "class", "doc": "

Estimates dataset statistics and computes sample statistics efficiently

\n"}, "bioimageio.core.stat_calculators.StatsCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tmeasures: Collection[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]],\tinitial_dataset_measures: Optional[Mapping[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]]] = None)"}, "bioimageio.core.stat_calculators.StatsCalculator.sample_count": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.sample_count", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.sample_count", "kind": "variable", "doc": "

\n"}, "bioimageio.core.stat_calculators.StatsCalculator.has_dataset_measures": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.has_dataset_measures", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.has_dataset_measures", "kind": "variable", "doc": "

\n"}, "bioimageio.core.stat_calculators.StatsCalculator.update": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.update", "kind": "function", "doc": "

\n", "signature": "(\tself,\tsample: Union[bioimageio.core.sample.Sample, Iterable[bioimageio.core.sample.Sample]]) -> None:", "funcdef": "def"}, "bioimageio.core.stat_calculators.StatsCalculator.finalize": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.finalize", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.finalize", "kind": "function", "doc": "

returns aggregated dataset statistics

\n", "signature": "(\tself) -> Dict[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.StatsCalculator.update_and_get_all": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.update_and_get_all", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.update_and_get_all", "kind": "function", "doc": "

Returns sample as well as updated dataset statistics

\n", "signature": "(\tself,\tsample: Union[bioimageio.core.sample.Sample, Iterable[bioimageio.core.sample.Sample]]) -> Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.StatsCalculator.skip_update_and_get_all": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.skip_update_and_get_all", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.skip_update_and_get_all", "kind": "function", "doc": "

Returns sample as well as previously computed dataset statistics

\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.get_measure_calculators": {"fullname": "bioimageio.core.stat_calculators.get_measure_calculators", "modulename": "bioimageio.core.stat_calculators", "qualname": "get_measure_calculators", "kind": "function", "doc": "

determines which calculators are needed to compute the required measures efficiently

\n", "signature": "(\trequired_measures: Iterable[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]) -> Tuple[List[Union[bioimageio.core.stat_calculators.MeanCalculator, bioimageio.core.stat_calculators.MeanVarStdCalculator, bioimageio.core.stat_calculators.SamplePercentilesCalculator, bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator]], List[Union[bioimageio.core.stat_calculators.MeanCalculator, bioimageio.core.stat_calculators.MeanVarStdCalculator, bioimageio.core.stat_calculators.MeanPercentilesCalculator]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.compute_dataset_measures": {"fullname": "bioimageio.core.stat_calculators.compute_dataset_measures", "modulename": "bioimageio.core.stat_calculators", "qualname": "compute_dataset_measures", "kind": "function", "doc": "

compute all dataset measures for the given dataset

\n", "signature": "(\tmeasures: Iterable[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]],\tdataset: Iterable[bioimageio.core.sample.Sample]) -> Dict[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.compute_sample_measures": {"fullname": "bioimageio.core.stat_calculators.compute_sample_measures", "modulename": "bioimageio.core.stat_calculators", "qualname": "compute_sample_measures", "kind": "function", "doc": "

compute all sample measures for the given sample

\n", "signature": "(\tmeasures: Iterable[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]],\tsample: bioimageio.core.sample.Sample) -> Dict[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.compute_measures": {"fullname": "bioimageio.core.stat_calculators.compute_measures", "modulename": "bioimageio.core.stat_calculators", "qualname": "compute_measures", "kind": "function", "doc": "

compute all measures for the given dataset\nsample measures are computed for the last sample in dataset

\n", "signature": "(\tmeasures: Iterable[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]],\tdataset: Iterable[bioimageio.core.sample.Sample]) -> Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.TDigest": {"fullname": "bioimageio.core.stat_calculators.TDigest", "modulename": "bioimageio.core.stat_calculators", "qualname": "TDigest", "kind": "class", "doc": "

\n"}, "bioimageio.core.stat_calculators.TDigest.update": {"fullname": "bioimageio.core.stat_calculators.TDigest.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "TDigest.update", "kind": "function", "doc": "

\n", "signature": "(self, obj: Any):", "funcdef": "def"}, "bioimageio.core.stat_calculators.TDigest.quantile": {"fullname": "bioimageio.core.stat_calculators.TDigest.quantile", "modulename": "bioimageio.core.stat_calculators", "qualname": "TDigest.quantile", "kind": "function", "doc": "

\n", "signature": "(self, q: Any) -> Any:", "funcdef": "def"}, "bioimageio.core.stat_calculators.DatasetPercentilesCalculator": {"fullname": "bioimageio.core.stat_calculators.DatasetPercentilesCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "DatasetPercentilesCalculator", "kind": "variable", "doc": "

\n", "annotation": ": Type[Union[bioimageio.core.stat_calculators.MeanPercentilesCalculator, bioimageio.core.stat_calculators.CrickPercentilesCalculator]]", "default_value": "<class 'bioimageio.core.stat_calculators.MeanPercentilesCalculator'>"}, "bioimageio.core.stat_measures": {"fullname": "bioimageio.core.stat_measures", "modulename": "bioimageio.core.stat_measures", "kind": "module", "doc": "

\n"}, "bioimageio.core.stat_measures.tensor_custom_before_validator": {"fullname": "bioimageio.core.stat_measures.tensor_custom_before_validator", "modulename": "bioimageio.core.stat_measures", "qualname": "tensor_custom_before_validator", "kind": "function", "doc": "

\n", "signature": "(data: Union[bioimageio.core.tensor.Tensor, Mapping[str, Any]]):", "funcdef": "def"}, "bioimageio.core.stat_measures.tensor_custom_serializer": {"fullname": "bioimageio.core.stat_measures.tensor_custom_serializer", "modulename": "bioimageio.core.stat_measures", "qualname": "tensor_custom_serializer", "kind": "function", "doc": "

\n", "signature": "(t: bioimageio.core.tensor.Tensor) -> Dict[str, Any]:", "funcdef": "def"}, "bioimageio.core.stat_measures.MeasureValue": {"fullname": "bioimageio.core.stat_measures.MeasureValue", "modulename": "bioimageio.core.stat_measures", "qualname": "MeasureValue", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[float, typing.Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]"}, "bioimageio.core.stat_measures.SampleLike": {"fullname": "bioimageio.core.stat_measures.SampleLike", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleLike", "kind": "class", "doc": "

Base class for protocol classes.

\n\n

Protocol classes are defined as::

\n\n
class Proto(Protocol):\n    def meth(self) -> int:\n        ...\n
\n\n

Such classes are primarily used with static type checkers that recognize\nstructural subtyping (static duck-typing).

\n\n

For example::

\n\n
class C:\n    def meth(self) -> int:\n        return 0\n\ndef func(x: Proto) -> int:\n    return x.meth()\n\nfunc(C())  # Passes static type check\n
\n\n

See PEP 544 for details. Protocol classes decorated with\n@typing.runtime_checkable act as simple-minded runtime protocols that check\nonly the presence of given attributes, ignoring their type signatures.\nProtocol classes can be generic, they are defined as::

\n\n
class GenProto[T](Protocol):\n    def meth(self) -> T:\n        ...\n
\n", "bases": "typing.Protocol"}, "bioimageio.core.stat_measures.SampleLike.__init__": {"fullname": "bioimageio.core.stat_measures.SampleLike.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleLike.__init__", "kind": "function", "doc": "

\n", "signature": "(*args, **kwargs)"}, "bioimageio.core.stat_measures.SampleLike.members": {"fullname": "bioimageio.core.stat_measures.SampleLike.members", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleLike.members", "kind": "variable", "doc": "

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.tensor.Tensor]"}, "bioimageio.core.stat_measures.MeasureBase": {"fullname": "bioimageio.core.stat_measures.MeasureBase", "modulename": "bioimageio.core.stat_measures", "qualname": "MeasureBase", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.9/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of the class variables defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The synthesized __init__ [Signature][inspect.Signature] of the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The core schema of the model.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a [`RootModel`][pydantic.root_model.RootModel].\n__pydantic_serializer__: The `pydantic-core` `SchemaSerializer` used to dump instances of the model.\n__pydantic_validator__: The `pydantic-core` `SchemaValidator` used to validate instances of the model.\n\n__pydantic_extra__: A dictionary containing extra values, if [`extra`][pydantic.config.ConfigDict.extra]\n    is set to `'allow'`.\n__pydantic_fields_set__: The names of fields explicitly set during instantiation.\n__pydantic_private__: Values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "bioimageio.core.stat_measures.MeasureBase.member_id": {"fullname": "bioimageio.core.stat_measures.MeasureBase.member_id", "modulename": "bioimageio.core.stat_measures", "qualname": "MeasureBase.member_id", "kind": "variable", "doc": "

\n", "annotation": ": bioimageio.spec.model.v0_5.TensorId"}, "bioimageio.core.stat_measures.MeasureBase.model_config": {"fullname": "bioimageio.core.stat_measures.MeasureBase.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "MeasureBase.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.MeasureBase.model_fields": {"fullname": "bioimageio.core.stat_measures.MeasureBase.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "MeasureBase.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True)}"}, "bioimageio.core.stat_measures.MeasureBase.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.MeasureBase.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "MeasureBase.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.SampleMeasureBase": {"fullname": "bioimageio.core.stat_measures.SampleMeasureBase", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMeasureBase", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.9/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of the class variables defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The synthesized __init__ [Signature][inspect.Signature] of the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The core schema of the model.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a [`RootModel`][pydantic.root_model.RootModel].\n__pydantic_serializer__: The `pydantic-core` `SchemaSerializer` used to dump instances of the model.\n__pydantic_validator__: The `pydantic-core` `SchemaValidator` used to validate instances of the model.\n\n__pydantic_extra__: A dictionary containing extra values, if [`extra`][pydantic.config.ConfigDict.extra]\n    is set to `'allow'`.\n__pydantic_fields_set__: The names of fields explicitly set during instantiation.\n__pydantic_private__: Values of private attributes set on the model instance.\n
\n", "bases": "MeasureBase, abc.ABC"}, "bioimageio.core.stat_measures.SampleMeasureBase.scope": {"fullname": "bioimageio.core.stat_measures.SampleMeasureBase.scope", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMeasureBase.scope", "kind": "variable", "doc": "

\n", "annotation": ": Literal['sample']"}, "bioimageio.core.stat_measures.SampleMeasureBase.compute": {"fullname": "bioimageio.core.stat_measures.SampleMeasureBase.compute", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMeasureBase.compute", "kind": "function", "doc": "

compute the measure

\n", "signature": "(\tself,\tsample: bioimageio.core.stat_measures.SampleLike) -> Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]:", "funcdef": "def"}, "bioimageio.core.stat_measures.SampleMeasureBase.model_config": {"fullname": "bioimageio.core.stat_measures.SampleMeasureBase.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMeasureBase.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.SampleMeasureBase.model_fields": {"fullname": "bioimageio.core.stat_measures.SampleMeasureBase.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMeasureBase.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True), 'scope': FieldInfo(annotation=Literal['sample'], required=False, default='sample')}"}, "bioimageio.core.stat_measures.SampleMeasureBase.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.SampleMeasureBase.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMeasureBase.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.DatasetMeasureBase": {"fullname": "bioimageio.core.stat_measures.DatasetMeasureBase", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMeasureBase", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.9/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of the class variables defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The synthesized __init__ [Signature][inspect.Signature] of the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The core schema of the model.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a [`RootModel`][pydantic.root_model.RootModel].\n__pydantic_serializer__: The `pydantic-core` `SchemaSerializer` used to dump instances of the model.\n__pydantic_validator__: The `pydantic-core` `SchemaValidator` used to validate instances of the model.\n\n__pydantic_extra__: A dictionary containing extra values, if [`extra`][pydantic.config.ConfigDict.extra]\n    is set to `'allow'`.\n__pydantic_fields_set__: The names of fields explicitly set during instantiation.\n__pydantic_private__: Values of private attributes set on the model instance.\n
\n", "bases": "MeasureBase, abc.ABC"}, "bioimageio.core.stat_measures.DatasetMeasureBase.scope": {"fullname": "bioimageio.core.stat_measures.DatasetMeasureBase.scope", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMeasureBase.scope", "kind": "variable", "doc": "

\n", "annotation": ": Literal['dataset']"}, "bioimageio.core.stat_measures.DatasetMeasureBase.model_config": {"fullname": "bioimageio.core.stat_measures.DatasetMeasureBase.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMeasureBase.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.DatasetMeasureBase.model_fields": {"fullname": "bioimageio.core.stat_measures.DatasetMeasureBase.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMeasureBase.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True), 'scope': FieldInfo(annotation=Literal['dataset'], required=False, default='dataset')}"}, "bioimageio.core.stat_measures.DatasetMeasureBase.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.DatasetMeasureBase.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMeasureBase.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.SampleMean": {"fullname": "bioimageio.core.stat_measures.SampleMean", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMean", "kind": "class", "doc": "

The mean value of a single tensor

\n", "bases": "_Mean, SampleMeasureBase"}, "bioimageio.core.stat_measures.SampleMean.compute": {"fullname": "bioimageio.core.stat_measures.SampleMean.compute", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMean.compute", "kind": "function", "doc": "

compute the measure

\n", "signature": "(\tself,\tsample: bioimageio.core.stat_measures.SampleLike) -> Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]:", "funcdef": "def"}, "bioimageio.core.stat_measures.SampleMean.model_post_init": {"fullname": "bioimageio.core.stat_measures.SampleMean.model_post_init", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMean.model_post_init", "kind": "function", "doc": "

Override this method to perform additional initialization after __init__ and model_construct.\nThis is useful if you want to do some validation that requires the entire model to be initialized.

\n", "signature": "(self, _SampleMean__context: Any):", "funcdef": "def"}, "bioimageio.core.stat_measures.SampleMean.model_config": {"fullname": "bioimageio.core.stat_measures.SampleMean.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMean.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.SampleMean.model_fields": {"fullname": "bioimageio.core.stat_measures.SampleMean.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMean.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True), 'scope': FieldInfo(annotation=Literal['sample'], required=False, default='sample'), 'name': FieldInfo(annotation=Literal['mean'], required=False, default='mean'), 'axes': FieldInfo(annotation=Union[Tuple[AxisId, ...], NoneType], required=False, default=None)}"}, "bioimageio.core.stat_measures.SampleMean.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.SampleMean.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMean.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.DatasetMean": {"fullname": "bioimageio.core.stat_measures.DatasetMean", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMean", "kind": "class", "doc": "

The mean value across multiple samples

\n", "bases": "_Mean, DatasetMeasureBase"}, "bioimageio.core.stat_measures.DatasetMean.model_post_init": {"fullname": "bioimageio.core.stat_measures.DatasetMean.model_post_init", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMean.model_post_init", "kind": "function", "doc": "

Override this method to perform additional initialization after __init__ and model_construct.\nThis is useful if you want to do some validation that requires the entire model to be initialized.

\n", "signature": "(self, _DatasetMean__context: Any):", "funcdef": "def"}, "bioimageio.core.stat_measures.DatasetMean.model_config": {"fullname": "bioimageio.core.stat_measures.DatasetMean.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMean.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.DatasetMean.model_fields": {"fullname": "bioimageio.core.stat_measures.DatasetMean.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMean.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True), 'scope': FieldInfo(annotation=Literal['dataset'], required=False, default='dataset'), 'name': FieldInfo(annotation=Literal['mean'], required=False, default='mean'), 'axes': FieldInfo(annotation=Union[Tuple[AxisId, ...], NoneType], required=False, default=None)}"}, "bioimageio.core.stat_measures.DatasetMean.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.DatasetMean.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMean.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.SampleStd": {"fullname": "bioimageio.core.stat_measures.SampleStd", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleStd", "kind": "class", "doc": "

The standard deviation of a single tensor

\n", "bases": "_Std, SampleMeasureBase"}, "bioimageio.core.stat_measures.SampleStd.compute": {"fullname": "bioimageio.core.stat_measures.SampleStd.compute", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleStd.compute", "kind": "function", "doc": "

compute the measure

\n", "signature": "(\tself,\tsample: bioimageio.core.stat_measures.SampleLike) -> Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]:", "funcdef": "def"}, "bioimageio.core.stat_measures.SampleStd.model_post_init": {"fullname": "bioimageio.core.stat_measures.SampleStd.model_post_init", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleStd.model_post_init", "kind": "function", "doc": "

Override this method to perform additional initialization after __init__ and model_construct.\nThis is useful if you want to do some validation that requires the entire model to be initialized.

\n", "signature": "(self, _SampleStd__context: Any):", "funcdef": "def"}, "bioimageio.core.stat_measures.SampleStd.model_config": {"fullname": "bioimageio.core.stat_measures.SampleStd.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleStd.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.SampleStd.model_fields": {"fullname": "bioimageio.core.stat_measures.SampleStd.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleStd.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True), 'scope': FieldInfo(annotation=Literal['sample'], required=False, default='sample'), 'name': FieldInfo(annotation=Literal['std'], required=False, default='std'), 'axes': FieldInfo(annotation=Union[Tuple[AxisId, ...], NoneType], required=False, default=None)}"}, "bioimageio.core.stat_measures.SampleStd.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.SampleStd.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleStd.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.DatasetStd": {"fullname": "bioimageio.core.stat_measures.DatasetStd", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetStd", "kind": "class", "doc": "

The standard deviation across multiple samples

\n", "bases": "_Std, DatasetMeasureBase"}, "bioimageio.core.stat_measures.DatasetStd.model_post_init": {"fullname": "bioimageio.core.stat_measures.DatasetStd.model_post_init", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetStd.model_post_init", "kind": "function", "doc": "

Override this method to perform additional initialization after __init__ and model_construct.\nThis is useful if you want to do some validation that requires the entire model to be initialized.

\n", "signature": "(self, _DatasetStd__context: Any):", "funcdef": "def"}, "bioimageio.core.stat_measures.DatasetStd.model_config": {"fullname": "bioimageio.core.stat_measures.DatasetStd.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetStd.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.DatasetStd.model_fields": {"fullname": "bioimageio.core.stat_measures.DatasetStd.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetStd.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True), 'scope': FieldInfo(annotation=Literal['dataset'], required=False, default='dataset'), 'name': FieldInfo(annotation=Literal['std'], required=False, default='std'), 'axes': FieldInfo(annotation=Union[Tuple[AxisId, ...], NoneType], required=False, default=None)}"}, "bioimageio.core.stat_measures.DatasetStd.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.DatasetStd.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetStd.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.SampleVar": {"fullname": "bioimageio.core.stat_measures.SampleVar", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleVar", "kind": "class", "doc": "

The variance of a single tensor

\n", "bases": "_Var, SampleMeasureBase"}, "bioimageio.core.stat_measures.SampleVar.compute": {"fullname": "bioimageio.core.stat_measures.SampleVar.compute", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleVar.compute", "kind": "function", "doc": "

compute the measure

\n", "signature": "(\tself,\tsample: bioimageio.core.stat_measures.SampleLike) -> Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]:", "funcdef": "def"}, "bioimageio.core.stat_measures.SampleVar.model_post_init": {"fullname": "bioimageio.core.stat_measures.SampleVar.model_post_init", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleVar.model_post_init", "kind": "function", "doc": "

Override this method to perform additional initialization after __init__ and model_construct.\nThis is useful if you want to do some validation that requires the entire model to be initialized.

\n", "signature": "(self, _SampleVar__context: Any):", "funcdef": "def"}, "bioimageio.core.stat_measures.SampleVar.model_config": {"fullname": "bioimageio.core.stat_measures.SampleVar.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleVar.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.SampleVar.model_fields": {"fullname": "bioimageio.core.stat_measures.SampleVar.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleVar.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True), 'scope': FieldInfo(annotation=Literal['sample'], required=False, default='sample'), 'name': FieldInfo(annotation=Literal['var'], required=False, default='var'), 'axes': FieldInfo(annotation=Union[Tuple[AxisId, ...], NoneType], required=False, default=None)}"}, "bioimageio.core.stat_measures.SampleVar.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.SampleVar.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleVar.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.DatasetVar": {"fullname": "bioimageio.core.stat_measures.DatasetVar", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetVar", "kind": "class", "doc": "

The variance across multiple samples

\n", "bases": "_Var, DatasetMeasureBase"}, "bioimageio.core.stat_measures.DatasetVar.model_post_init": {"fullname": "bioimageio.core.stat_measures.DatasetVar.model_post_init", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetVar.model_post_init", "kind": "function", "doc": "

Override this method to perform additional initialization after __init__ and model_construct.\nThis is useful if you want to do some validation that requires the entire model to be initialized.

\n", "signature": "(self, _DatasetVar__context: Any):", "funcdef": "def"}, "bioimageio.core.stat_measures.DatasetVar.model_config": {"fullname": "bioimageio.core.stat_measures.DatasetVar.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetVar.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.DatasetVar.model_fields": {"fullname": "bioimageio.core.stat_measures.DatasetVar.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetVar.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True), 'scope': FieldInfo(annotation=Literal['dataset'], required=False, default='dataset'), 'name': FieldInfo(annotation=Literal['var'], required=False, default='var'), 'axes': FieldInfo(annotation=Union[Tuple[AxisId, ...], NoneType], required=False, default=None)}"}, "bioimageio.core.stat_measures.DatasetVar.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.DatasetVar.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetVar.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.SampleQuantile": {"fullname": "bioimageio.core.stat_measures.SampleQuantile", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleQuantile", "kind": "class", "doc": "

The nth percentile of a single tensor

\n", "bases": "_Quantile, SampleMeasureBase"}, "bioimageio.core.stat_measures.SampleQuantile.compute": {"fullname": "bioimageio.core.stat_measures.SampleQuantile.compute", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleQuantile.compute", "kind": "function", "doc": "

compute the measure

\n", "signature": "(\tself,\tsample: bioimageio.core.stat_measures.SampleLike) -> Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7fb73cf53ec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7fb73cd74220>, return_type=PydanticUndefined, when_used='always')]]:", "funcdef": "def"}, "bioimageio.core.stat_measures.SampleQuantile.model_post_init": {"fullname": "bioimageio.core.stat_measures.SampleQuantile.model_post_init", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleQuantile.model_post_init", "kind": "function", "doc": "

Override this method to perform additional initialization after __init__ and model_construct.\nThis is useful if you want to do some validation that requires the entire model to be initialized.

\n", "signature": "(self, _SampleQuantile__context: Any):", "funcdef": "def"}, "bioimageio.core.stat_measures.SampleQuantile.model_config": {"fullname": "bioimageio.core.stat_measures.SampleQuantile.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleQuantile.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.SampleQuantile.model_fields": {"fullname": "bioimageio.core.stat_measures.SampleQuantile.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleQuantile.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True), 'scope': FieldInfo(annotation=Literal['sample'], required=False, default='sample'), 'name': FieldInfo(annotation=Literal['quantile'], required=False, default='quantile'), 'q': FieldInfo(annotation=float, required=True), 'axes': FieldInfo(annotation=Union[Tuple[AxisId, ...], NoneType], required=False, default=None)}"}, "bioimageio.core.stat_measures.SampleQuantile.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.SampleQuantile.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleQuantile.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.DatasetPercentile": {"fullname": "bioimageio.core.stat_measures.DatasetPercentile", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetPercentile", "kind": "class", "doc": "

The nth percentile across multiple samples

\n", "bases": "_Quantile, DatasetMeasureBase"}, "bioimageio.core.stat_measures.DatasetPercentile.model_post_init": {"fullname": "bioimageio.core.stat_measures.DatasetPercentile.model_post_init", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetPercentile.model_post_init", "kind": "function", "doc": "

Override this method to perform additional initialization after __init__ and model_construct.\nThis is useful if you want to do some validation that requires the entire model to be initialized.

\n", "signature": "(self, _DatasetPercentile__context: Any):", "funcdef": "def"}, "bioimageio.core.stat_measures.DatasetPercentile.model_config": {"fullname": "bioimageio.core.stat_measures.DatasetPercentile.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetPercentile.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.DatasetPercentile.model_fields": {"fullname": "bioimageio.core.stat_measures.DatasetPercentile.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetPercentile.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True), 'scope': FieldInfo(annotation=Literal['dataset'], required=False, default='dataset'), 'name': FieldInfo(annotation=Literal['quantile'], required=False, default='quantile'), 'q': FieldInfo(annotation=float, required=True), 'axes': FieldInfo(annotation=Union[Tuple[AxisId, ...], NoneType], required=False, default=None)}"}, "bioimageio.core.stat_measures.DatasetPercentile.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.DatasetPercentile.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetPercentile.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.SampleMeasure": {"fullname": "bioimageio.core.stat_measures.SampleMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMeasure", "kind": "variable", "doc": "

\n", "default_value": "typing.Annotated[typing.Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]"}, "bioimageio.core.stat_measures.DatasetMeasure": {"fullname": "bioimageio.core.stat_measures.DatasetMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMeasure", "kind": "variable", "doc": "

\n", "default_value": "typing.Annotated[typing.Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]"}, "bioimageio.core.stat_measures.Measure": {"fullname": "bioimageio.core.stat_measures.Measure", "modulename": "bioimageio.core.stat_measures", "qualname": "Measure", "kind": "variable", "doc": "

\n", "default_value": "typing.Annotated[typing.Union[typing.Annotated[typing.Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]"}, "bioimageio.core.stat_measures.Stat": {"fullname": "bioimageio.core.stat_measures.Stat", "modulename": "bioimageio.core.stat_measures", "qualname": "Stat", "kind": "variable", "doc": "

\n", "default_value": "typing.Dict[typing.Annotated[typing.Union[typing.Annotated[typing.Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Union[float, typing.Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]]"}, "bioimageio.core.stat_measures.MeanMeasure": {"fullname": "bioimageio.core.stat_measures.MeanMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "MeanMeasure", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean]"}, "bioimageio.core.stat_measures.StdMeasure": {"fullname": "bioimageio.core.stat_measures.StdMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "StdMeasure", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd]"}, "bioimageio.core.stat_measures.VarMeasure": {"fullname": "bioimageio.core.stat_measures.VarMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "VarMeasure", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.DatasetVar]"}, "bioimageio.core.stat_measures.PercentileMeasure": {"fullname": "bioimageio.core.stat_measures.PercentileMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "PercentileMeasure", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile]"}, "bioimageio.core.tensor": {"fullname": "bioimageio.core.tensor", "modulename": "bioimageio.core.tensor", "kind": "module", "doc": "

\n"}, "bioimageio.core.tensor.Tensor": {"fullname": "bioimageio.core.tensor.Tensor", "modulename": "bioimageio.core.tensor", "qualname": "Tensor", "kind": "class", "doc": "

A wrapper around an xr.DataArray for better integration with bioimageio.spec\nand improved type annotations.

\n", "bases": "bioimageio.core._magic_tensor_ops.MagicTensorOpsMixin"}, "bioimageio.core.tensor.Tensor.__init__": {"fullname": "bioimageio.core.tensor.Tensor.__init__", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.__init__", "kind": "function", "doc": "

\n", "signature": "(\tarray: numpy.ndarray[typing.Any, numpy.dtype[typing.Any]],\tdims: Sequence[Union[bioimageio.spec.model.v0_5.AxisId, Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis]])"}, "bioimageio.core.tensor.Tensor.from_xarray": {"fullname": "bioimageio.core.tensor.Tensor.from_xarray", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.from_xarray", "kind": "function", "doc": "

create a Tensor from an xarray data array

\n\n

note for internal use: this factory method is round-trip save\n for any Tensor's data property (an xarray.DataArray).

\n", "signature": "(cls, data_array: xarray.core.dataarray.DataArray) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.from_numpy": {"fullname": "bioimageio.core.tensor.Tensor.from_numpy", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.from_numpy", "kind": "function", "doc": "

create a Tensor from a numpy array

\n\n

Args:\n array: the nd numpy array\n axes: A description of the array's axes,\n if None axes are guessed (which might fail and raise a ValueError.)

\n\n

Raises:\n ValueError: if axes is None and axes guessing fails.

\n", "signature": "(\tcls,\tarray: numpy.ndarray[typing.Any, numpy.dtype[typing.Any]],\t*,\tdims: Union[bioimageio.spec.model.v0_5.AxisId, Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis, Sequence[Union[bioimageio.spec.model.v0_5.AxisId, Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis]], NoneType]) -> bioimageio.core.tensor.Tensor:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.data": {"fullname": "bioimageio.core.tensor.Tensor.data", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.data", "kind": "variable", "doc": "

\n"}, "bioimageio.core.tensor.Tensor.dims": {"fullname": "bioimageio.core.tensor.Tensor.dims", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.dims", "kind": "variable", "doc": "

Tuple of dimension names associated with this tensor.

\n"}, "bioimageio.core.tensor.Tensor.tagged_shape": {"fullname": "bioimageio.core.tensor.Tensor.tagged_shape", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.tagged_shape", "kind": "variable", "doc": "

(alias for sizes) Ordered, immutable mapping from axis ids to lengths.

\n"}, "bioimageio.core.tensor.Tensor.shape_tuple": {"fullname": "bioimageio.core.tensor.Tensor.shape_tuple", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.shape_tuple", "kind": "variable", "doc": "

Tuple of tensor axes lengths

\n"}, "bioimageio.core.tensor.Tensor.size": {"fullname": "bioimageio.core.tensor.Tensor.size", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.size", "kind": "variable", "doc": "

Number of elements in the tensor.

\n\n

Equal to math.prod(tensor.shape), i.e., the product of the tensors\u2019 dimensions.

\n"}, "bioimageio.core.tensor.Tensor.sum": {"fullname": "bioimageio.core.tensor.Tensor.sum", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.sum", "kind": "function", "doc": "

Reduce this Tensor's data by applying sum along some dimension(s).

\n", "signature": "(\tself,\tdim: Union[bioimageio.spec.model.v0_5.AxisId, Sequence[bioimageio.spec.model.v0_5.AxisId], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.ndim": {"fullname": "bioimageio.core.tensor.Tensor.ndim", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.ndim", "kind": "variable", "doc": "

Number of tensor dimensions.

\n"}, "bioimageio.core.tensor.Tensor.dtype": {"fullname": "bioimageio.core.tensor.Tensor.dtype", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.dtype", "kind": "variable", "doc": "

\n", "annotation": ": Literal['bool', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64']"}, "bioimageio.core.tensor.Tensor.sizes": {"fullname": "bioimageio.core.tensor.Tensor.sizes", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.sizes", "kind": "variable", "doc": "

Ordered, immutable mapping from axis ids to axis lengths.

\n"}, "bioimageio.core.tensor.Tensor.astype": {"fullname": "bioimageio.core.tensor.Tensor.astype", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.astype", "kind": "function", "doc": "

Return tensor cast to dtype

\n\n

note: if dtype is already satisfied copy if copy

\n", "signature": "(\tself,\tdtype: Literal['bool', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64'],\t*,\tcopy: bool = False):", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.clip": {"fullname": "bioimageio.core.tensor.Tensor.clip", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.clip", "kind": "function", "doc": "

Return a tensor whose values are limited to [min, max].\nAt least one of max or min must be given.

\n", "signature": "(self, min: Optional[float] = None, max: Optional[float] = None):", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.crop_to": {"fullname": "bioimageio.core.tensor.Tensor.crop_to", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.crop_to", "kind": "function", "doc": "

crop to match sizes

\n", "signature": "(\tself,\tsizes: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\tcrop_where: Union[Literal['left', 'right', 'left_and_right'], Mapping[bioimageio.spec.model.v0_5.AxisId, Literal['left', 'right', 'left_and_right']]] = 'left_and_right') -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.expand_dims": {"fullname": "bioimageio.core.tensor.Tensor.expand_dims", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.expand_dims", "kind": "function", "doc": "

\n", "signature": "(\tself,\tdims: Union[Sequence[bioimageio.spec.model.v0_5.AxisId], Mapping[bioimageio.spec.model.v0_5.AxisId, int]]) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.mean": {"fullname": "bioimageio.core.tensor.Tensor.mean", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.mean", "kind": "function", "doc": "

\n", "signature": "(\tself,\tdim: Union[bioimageio.spec.model.v0_5.AxisId, Sequence[bioimageio.spec.model.v0_5.AxisId], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.std": {"fullname": "bioimageio.core.tensor.Tensor.std", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.std", "kind": "function", "doc": "

\n", "signature": "(\tself,\tdim: Union[bioimageio.spec.model.v0_5.AxisId, Sequence[bioimageio.spec.model.v0_5.AxisId], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.var": {"fullname": "bioimageio.core.tensor.Tensor.var", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.var", "kind": "function", "doc": "

\n", "signature": "(\tself,\tdim: Union[bioimageio.spec.model.v0_5.AxisId, Sequence[bioimageio.spec.model.v0_5.AxisId], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.pad": {"fullname": "bioimageio.core.tensor.Tensor.pad", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.pad", "kind": "function", "doc": "

\n", "signature": "(\tself,\tpad_width: Mapping[bioimageio.spec.model.v0_5.AxisId, Union[int, Tuple[int, int], bioimageio.core.common.PadWidth]],\tmode: Literal['edge', 'reflect', 'symmetric'] = 'symmetric') -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.pad_to": {"fullname": "bioimageio.core.tensor.Tensor.pad_to", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.pad_to", "kind": "function", "doc": "

pad tensor to match sizes

\n", "signature": "(\tself,\tsizes: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\tpad_where: Union[Literal['left', 'right', 'left_and_right'], Mapping[bioimageio.spec.model.v0_5.AxisId, Literal['left', 'right', 'left_and_right']]] = 'left_and_right',\tmode: Literal['edge', 'reflect', 'symmetric'] = 'symmetric') -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.quantile": {"fullname": "bioimageio.core.tensor.Tensor.quantile", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.quantile", "kind": "function", "doc": "

\n", "signature": "(\tself,\tq: Union[float, Sequence[float]],\tdim: Union[bioimageio.spec.model.v0_5.AxisId, Sequence[bioimageio.spec.model.v0_5.AxisId], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.resize_to": {"fullname": "bioimageio.core.tensor.Tensor.resize_to", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.resize_to", "kind": "function", "doc": "

return cropped/padded tensor with sizes

\n", "signature": "(\tself,\tsizes: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\t*,\tpad_where: Union[Literal['left', 'right', 'left_and_right'], Mapping[bioimageio.spec.model.v0_5.AxisId, Literal['left', 'right', 'left_and_right']]] = 'left_and_right',\tcrop_where: Union[Literal['left', 'right', 'left_and_right'], Mapping[bioimageio.spec.model.v0_5.AxisId, Literal['left', 'right', 'left_and_right']]] = 'left_and_right',\tpad_mode: Literal['edge', 'reflect', 'symmetric'] = 'symmetric'):", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.transpose": {"fullname": "bioimageio.core.tensor.Tensor.transpose", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.transpose", "kind": "function", "doc": "

return a transposed tensor

\n\n

Args:\n axes: the desired tensor axes

\n", "signature": "(self, axes: Sequence[bioimageio.spec.model.v0_5.AxisId]) -> Self:", "funcdef": "def"}, "bioimageio.core.utils": {"fullname": "bioimageio.core.utils", "modulename": "bioimageio.core.utils", "kind": "module", "doc": "

\n"}, "bioimageio.core.utils.testing": {"fullname": "bioimageio.core.utils.testing", "modulename": "bioimageio.core.utils.testing", "kind": "module", "doc": "

\n"}, "bioimageio.core.utils.testing.test_func": {"fullname": "bioimageio.core.utils.testing.test_func", "modulename": "bioimageio.core.utils.testing", "qualname": "test_func", "kind": "class", "doc": "

Base class for protocol classes.

\n\n

Protocol classes are defined as::

\n\n
class Proto(Protocol):\n    def meth(self) -> int:\n        ...\n
\n\n

Such classes are primarily used with static type checkers that recognize\nstructural subtyping (static duck-typing).

\n\n

For example::

\n\n
class C:\n    def meth(self) -> int:\n        return 0\n\ndef func(x: Proto) -> int:\n    return x.meth()\n\nfunc(C())  # Passes static type check\n
\n\n

See PEP 544 for details. Protocol classes decorated with\n@typing.runtime_checkable act as simple-minded runtime protocols that check\nonly the presence of given attributes, ignoring their type signatures.\nProtocol classes can be generic, they are defined as::

\n\n
class GenProto[T](Protocol):\n    def meth(self) -> T:\n        ...\n
\n", "bases": "typing.Protocol"}, "bioimageio.core.utils.testing.test_func.__init__": {"fullname": "bioimageio.core.utils.testing.test_func.__init__", "modulename": "bioimageio.core.utils.testing", "qualname": "test_func.__init__", "kind": "function", "doc": "

\n", "signature": "(*args, **kwargs)"}, "bioimageio.core.utils.testing.skip_on": {"fullname": "bioimageio.core.utils.testing.skip_on", "modulename": "bioimageio.core.utils.testing", "qualname": "skip_on", "kind": "function", "doc": "

adapted from https://stackoverflow.com/a/63522579

\n", "signature": "(exception: Type[Exception], reason: str):", "funcdef": "def"}, "bioimageio.core.weight_converter": {"fullname": "bioimageio.core.weight_converter", "modulename": "bioimageio.core.weight_converter", "kind": "module", "doc": "

coming soon

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"bioimageio.core.stat_measures.SampleMeasureBase.model_fields": {"tf": 1}, "bioimageio.core.stat_measures.SampleMeasureBase.model_computed_fields": {"tf": 1}, "bioimageio.core.stat_measures.DatasetMeasureBase": {"tf": 1.4142135623730951}, "bioimageio.core.stat_measures.DatasetMeasureBase.model_fields": {"tf": 1}, "bioimageio.core.stat_measures.DatasetMeasureBase.model_computed_fields": {"tf": 1}, "bioimageio.core.stat_measures.SampleMean.model_fields": {"tf": 1}, "bioimageio.core.stat_measures.SampleMean.model_computed_fields": {"tf": 1}, "bioimageio.core.stat_measures.DatasetMean.model_fields": {"tf": 1}, "bioimageio.core.stat_measures.DatasetMean.model_computed_fields": {"tf": 1}, "bioimageio.core.stat_measures.SampleStd.model_fields": {"tf": 1}, "bioimageio.core.stat_measures.SampleStd.model_computed_fields": {"tf": 1}, "bioimageio.core.stat_measures.DatasetStd.model_fields": {"tf": 1}, "bioimageio.core.stat_measures.DatasetStd.model_computed_fields": {"tf": 1}, 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{"tf": 1.4142135623730951}, "bioimageio.core.utils.testing.test_func": {"tf": 1.4142135623730951}}, "df": 2, "r": {"docs": {"bioimageio.core.tensor.Tensor": {"tf": 1}}, "df": 1}, "a": {"docs": {}, "df": 0, "r": {"docs": {}, "df": 0, "r": {"docs": {}, "df": 0, "a": {"docs": {}, "df": 0, "y": {"docs": {"bioimageio.core.tensor.Tensor.from_xarray": {"tf": 1.4142135623730951}}, "df": 1}}}}}}}}}, "pipeline": ["trimmer"], "_isPrebuiltIndex": true}; + /** pdoc search index */const docs = {"version": "0.9.5", "fields": ["qualname", "fullname", "annotation", "default_value", "signature", "bases", "doc"], "ref": "fullname", "documentStore": {"docs": {"bioimageio.core": {"fullname": "bioimageio.core", "modulename": "bioimageio.core", "kind": "module", "doc": "

\"License\"\n\"PyPI\"\n\"conda-version\"\n\"downloads\"\n\"conda-forge\n\"code

\n\n

core-bioimage-io-python

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Python specific core utilities for bioimage.io resources (in particular models).

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Get started

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To get started we recommend installing bioimageio.core with conda together with a deep\nlearning framework, e.g. pytorch, and run a few bioimageio commands to see what\nbioimage.core has to offer:

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    \n

  1. install with conda (for more details on conda environments, checkout the conda docs)

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    conda install -c conda-forge bioimageio.core pytorch\n
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    2. \n\n

  2. test a model

    \n\n
    \n
    $ bioimageio test powerful-chipmunk\n...\n
    \n
    \n\n

    \n(Click to expand output)

    \n\n
    \n
      \u2714\ufe0f                 bioimageio validation passed\n\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\n  source            https://uk1s3.embassy.ebi.ac.uk/public-datasets/bioimage.io/powerful-chipmunk/1/files/rdf.yaml\n  format version    model 0.4.10\n  bioimageio.spec   0.5.3post4\n  bioimageio.core   0.6.8\n\n\n\n  \u2753   location                                     detail\n\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\n  \u2714\ufe0f                                                 initialized ModelDescr to describe model 0.4.10\n\n  \u2714\ufe0f                                                 bioimageio.spec format validation model 0.4.10\n  \ud83d\udd0d   context.perform_io_checks                    True\n  \ud83d\udd0d   context.root                                 https://uk1s3.embassy.ebi.ac.uk/public-datasets/bioimage.io/powerful-chipmunk/1/files\n  \ud83d\udd0d   context.known_files.weights.pt               3bd9c518c8473f1e35abb7624f82f3aa92f1015e66fb1f6a9d08444e1f2f5698\n  \ud83d\udd0d   context.known_files.weights-torchscript.pt   4e568fd81c0ffa06ce13061327c3f673e1bac808891135badd3b0fcdacee086b\n  \ud83d\udd0d   context.warning_level                        error\n\n  \u2714\ufe0f                                                 Reproduce test outputs from test inputs\n\n  \u2714\ufe0f                                                 Reproduce test outputs from test inputs\n
    \n
    \n\n

    \n\n

    or

    \n\n
    \n
    $ bioimageio test impartial-shrimp\n...\n
    \n
    \n\n

    (Click to expand output)

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    \n
      \u2714\ufe0f                 bioimageio validation passed\n\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\n  source            https://uk1s3.embassy.ebi.ac.uk/public-datasets/bioimage.io/impartial-shrimp/1.1/files/rdf.yaml\n  format version    model 0.5.3\n  bioimageio.spec   0.5.3.2\n  bioimageio.core   0.6.9\n\n\n  \u2753   location                    detail\n\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\n  \u2714\ufe0f                                initialized ModelDescr to describe model 0.5.3\n\n\n  \u2714\ufe0f                                bioimageio.spec format validation model 0.5.3\n\n  \ud83d\udd0d   context.perform_io_checks   False\n  \ud83d\udd0d   context.warning_level       error\n\n  \u2714\ufe0f                                Reproduce test outputs from test inputs (pytorch_state_dict)\n\n\n  \u2714\ufe0f                                Run pytorch_state_dict inference for inputs with batch_size: 1 and size parameter n:\n\n                                  0\n\n  \u2714\ufe0f                                Run pytorch_state_dict inference for inputs with batch_size: 2 and size parameter n:\n\n                                  0\n\n  \u2714\ufe0f                                Run pytorch_state_dict inference for inputs with batch_size: 1 and size parameter n:\n\n                                  1\n\n  \u2714\ufe0f                                Run pytorch_state_dict inference for inputs with batch_size: 2 and size parameter n:\n\n                                  1\n\n  \u2714\ufe0f                                Run pytorch_state_dict inference for inputs with batch_size: 1 and size parameter n:\n\n                                  2\n\n  \u2714\ufe0f                                Run pytorch_state_dict inference for inputs with batch_size: 2 and size parameter n:\n\n                                  2\n\n  \u2714\ufe0f                                Reproduce test outputs from test inputs (torchscript)\n\n\n  \u2714\ufe0f                                Run torchscript inference for inputs with batch_size: 1 and size parameter n: 0\n\n\n  \u2714\ufe0f                                Run torchscript inference for inputs with batch_size: 2 and size parameter n: 0\n\n\n  \u2714\ufe0f                                Run torchscript inference for inputs with batch_size: 1 and size parameter n: 1\n\n\n  \u2714\ufe0f                                Run torchscript inference for inputs with batch_size: 2 and size parameter n: 1\n\n\n  \u2714\ufe0f                                Run torchscript inference for inputs with batch_size: 1 and size parameter n: 2\n\n\n  \u2714\ufe0f                                Run torchscript inference for inputs with batch_size: 2 and size parameter n: 2\n
    \n
    \n\n

    3. \n
  3. run prediction on your data
    4. \n
\n\n
    \n

  • display the bioimageio-predict command help to get an overview:

    \n\n
    \n
    $ bioimageio predict --help\n...\n
    \n
    \n\n

    \n(Click to expand output)

    \n\n
    \n
    usage: bioimageio predict [-h] [--inputs Sequence[Union[str,Annotated[Tuple[str,...],MinLenmin_length=1]]]]\n                          [--outputs {str,Tuple[str,...]}] [--overwrite bool] [--blockwise bool] [--stats Path]\n                          [--preview bool]\n                          [--weight_format {typing.Literal['keras_hdf5','onnx','pytorch_state_dict','tensorflow_js','tensorflow_saved_model_bundle','torchscript'],any}]\n                          [--example bool]\n                          SOURCE\n\nbioimageio-predict - Run inference on your data with a bioimage.io model.\n\npositional arguments:\n  SOURCE                Url/path to a bioimageio.yaml/rdf.yaml file\n                        or a bioimage.io resource identifier, e.g. 'affable-shark'\n\noptional arguments:\n  -h, --help            show this help message and exit\n  --inputs Sequence[Union[str,Annotated[Tuple[str,...],MinLen(min_length=1)]]]\n                        Model input sample paths (for each input tensor)\n\n                        The input paths are expected to have shape...\n                        - (n_samples,) or (n_samples,1) for models expecting a single input tensor\n                        - (n_samples,) containing the substring '{input_id}', or\n                        - (n_samples, n_model_inputs) to provide each input tensor path explicitly.\n\n                        All substrings that are replaced by metadata from the model description:\n                        - '{model_id}'\n                        - '{input_id}'\n\n                        Example inputs to process sample 'a' and 'b'\n                        for a model expecting a 'raw' and a 'mask' input tensor:\n                        --inputs="[["a_raw.tif","a_mask.tif"],["b_raw.tif","b_mask.tif"]]"\n                        (Note that JSON double quotes need to be escaped.)\n\n                        Alternatively a `bioimageio-cli.yaml` (or `bioimageio-cli.json`) file\n                        may provide the arguments, e.g.:\n                        ```yaml\n                        inputs:\n                        - [a_raw.tif, a_mask.tif]\n                        - [b_raw.tif, b_mask.tif]\n                   \n
    \n
    \n\n
                        `.npy` and any file extension supported by imageio are supported.\n                    Aavailable formats are listed at\n                    https://imageio.readthedocs.io/en/stable/formats/index.html#all-formats.\n                    Some formats have additional dependencies.\n\n                    \u200a (default: ('{input_id}/001.tif',))\n
    \n\n

    --outputs {str,Tuple[str,...]}\n Model output path pattern (per output tensor)

    \n\n
                        All substrings that are replaced:\n                    - '{model_id}' (from model description)\n                    - '{output_id}' (from model description)\n                    - '{sample_id}' (extracted from input paths)\n\n                    \u200a (default: outputs_{model_id}/{output_id}/{sample_id}.tif)\n
    \n\n

    --overwrite bool allow overwriting existing output files (default: False)\n --blockwise bool process inputs blockwise (default: False)\n --stats Path path to dataset statistics\n (will be written if it does not exist,\n but the model requires statistical dataset measures)\n \u200a (default: dataset_statistics.json)\n --preview bool preview which files would be processed\n and what outputs would be generated. (default: False)\n --weight_format {typing.Literal['keras_hdf5','onnx','pytorch_state_dict','tensorflow_js','tensorflow_saved_model_bundle','torchscript'],any}\n The weight format to use. (default: any)\n --example bool generate and run an example

    \n\n
                        1. downloads example model inputs\n                    2. creates a `{model_id}_example` folder\n                    3. writes input arguments to `{model_id}_example/bioimageio-cli.yaml`\n                    4. executes a preview dry-run\n                    5. executes prediction with example input\n\n                    \u200a (default: False)\n
    • \n
\n\n
\n    </details>\n\n- create an example and run prediction locally!\n\n    ```console\n    $ bioimageio predict impartial-shrimp --example=True\n    ...\n
\n\n
<details>\n<summary>(Click to expand output)</summary>\n\n```console\n\ud83d\udec8 bioimageio prediction preview structure:\n{'{sample_id}': {'inputs': {'{input_id}': '<input path>'},\n                'outputs': {'{output_id}': '<output path>'}}}\n\ud83d\udd0e bioimageio prediction preview output:\n{'1': {'inputs': {'input0': 'impartial-shrimp_example/input0/001.tif'},\n      'outputs': {'output0': 'impartial-shrimp_example/outputs/output0/1.tif'}}}\npredict with impartial-shrimp: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 1/1 [00:21<00:00, 21.76s/sample]\n\ud83c\udf89 Sucessfully ran example prediction!\nTo predict the example input using the CLI example config file impartial-shrimp_example\\bioimageio-cli.yaml, execute `bioimageio predict` from impartial-shrimp_example:\n$ cd impartial-shrimp_example\n$ bioimageio predict \"impartial-shrimp\"\n\nAlternatively run the following command in the current workind directory, not the example folder:\n$ bioimageio predict --preview=False --overwrite=True --stats=\"impartial-shrimp_example/dataset_statistics.json\" --inputs=\"[[\\\"impartial-shrimp_example/input0/001.tif\\\"]]\" --outputs=\"impartial-shrimp_example/outputs/{output_id}/{sample_id}.tif\" \"impartial-shrimp\"\n(note that a local 'bioimageio-cli.json' or 'bioimageio-cli.yaml' may interfere with this)\n
\n\n
\n  </details>\n\n## Installation\n\n### Via Mamba/Conda\n\nThe `bioimageio.core` package can be installed from conda-forge via\n\n```console\nmamba install -c conda-forge bioimageio.core\n```\n\nIf you do not install any additional deep learning libraries, you will only be able to use general convenience\nfunctionality, but not any functionality for model prediction.\nTo install additional deep learning libraries use:\n\n- Pytorch/Torchscript:\n\n  CPU installation (if you don't have an nvidia graphics card):\n\n  ```console\n  mamba install -c pytorch -c conda-forge bioimageio.core pytorch torchvision cpuonly\n
\n\n

GPU installation (for cuda 11.6, please choose the appropriate cuda version for your system):

\n\n

\n
mamba install -c pytorch -c nvidia -c conda-forge bioimageio.core pytorch torchvision pytorch-cuda=11.8\n
\n

\n\n

Note that the pytorch installation instructions may change in the future. For the latest instructions please refer to pytorch.org.

\n\n
    \n

  • Tensorflow

    \n\n

    Currently only CPU version supported

    \n\n
    \n
    mamba install -c conda-forge bioimageio.core tensorflow\n
    \n
    • \n\n

  • ONNXRuntime

    \n\n

    Currently only cpu version supported

    \n\n
    \n
    mamba install -c conda-forge bioimageio.core onnxruntime\n
    \n
    • \n
\n\n

Via pip

\n\n

The package is also available via pip\n(e.g. with recommended extras onnx and pytorch):

\n\n
\n
pip install "bioimageio.core[onnx,pytorch]"\n
\n
\n\n

Set up Development Environment

\n\n

To set up a development conda environment run the following commands:

\n\n
\n
mamba env create -f dev/env.yaml\nmamba activate core\npip install -e . --no-deps\n
\n
\n\n

There are different environment files available that only install tensorflow or pytorch as dependencies.

\n\n

\ud83d\udcbb Use the Command Line Interface

\n\n

bioimageio.core installs a command line interface (CLI) for testing models and other functionality.\nYou can list all the available commands via:

\n\n
\n
bioimageio\n
\n
\n\n

CLI inputs from file

\n\n

For convenience the command line options (not arguments) may be given in a bioimageio-cli.json\nor bioimageio-cli.yaml file, e.g.:

\n\n
\n
# bioimageio-cli.yaml\ninputs: inputs/*_{tensor_id}.h5\noutputs: outputs_{model_id}/{sample_id}_{tensor_id}.h5\noverwrite: true\nblockwise: true\nstats: inputs/dataset_statistics.json\n
\n
\n\n

\ud83d\udc0d Use in Python

\n\n

bioimageio.core is a python package that implements prediction with bioimageio models\nincluding standardized pre- and postprocessing operations.\nThese models are described by---and can be loaded with---the bioimageio.spec package.

\n\n

In addition bioimageio.core provides functionality to convert model weight formats.

\n\n

To get an overview of this functionality, check out these example notebooks:

\n\n\n\n

and the developer documentation.

\n\n

Logging level

\n\n

bioimageio.spec and bioimageio.core use loguru for logging, hence the logging level\nmay be controlled with the LOGURU_LEVEL environment variable.

\n\n

Model Specification

\n\n

The model specification and its validation tools can be found at https://github.com/bioimage-io/spec-bioimage-io.

\n\n

Changelog

\n\n

0.6.9

\n\n
    \n
  • improve bioimageio command line interface (details in #157)\n
      \n
    • add predict command
      • \n
    • package command input path is now required
      • \n
    • \n
\n\n

0.6.8

\n\n
    \n
  • testing model inference will now check all weight formats\n(previously only the first one for which model adapter creation succeeded had been checked)
    • \n
  • fix predict with blocking (Thanks @thodkatz)
    • \n
\n\n

0.6.7

\n\n
    \n
  • predict() argument inputs may be sample
    • \n
\n\n

0.6.6

\n\n
    \n
  • add aliases to match previous API more closely
    • \n
\n\n

0.6.5

\n\n
    \n
  • improve adapter error messages
    • \n
\n\n

0.6.4

\n\n
    \n
  • add bioimageio validate-format command
    • \n
  • improve error messages and display of command results
    • \n
\n\n

0.6.3

\n\n
    \n
  • Fix #386
    • \n
  • (in model inference testing) stop assuming model inputs are tileable
    • \n
\n\n

0.6.2

\n\n\n\n

0.6.1

\n\n\n\n

0.6.0

\n\n
    \n
  • add compatibility with new bioimageio.spec 0.5 (0.5.2post1)
    • \n
  • improve interfaces
    • \n
\n\n

0.5.10

\n\n\n"}, "bioimageio.core.test_resource": {"fullname": "bioimageio.core.test_resource", "modulename": "bioimageio.core", "qualname": "test_resource", "kind": "function", "doc": "

Test a bioimage.io resource dynamically, e.g. prediction of test tensors for models

\n", "signature": "(\tsource: Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], Dict[str, YamlValue]],\t*,\tformat_version: Union[Literal['discover', 'latest'], str] = 'discover',\tweight_format: Optional[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']] = None,\tdevices: Optional[Sequence[str]] = None,\tabsolute_tolerance: float = 0.00015,\trelative_tolerance: float = 0.0001,\tdecimal: Optional[int] = None,\texpected_type: Optional[str] = None) -> bioimageio.spec.summary.ValidationSummary:", "funcdef": "def"}, "bioimageio.core.load_resource": {"fullname": "bioimageio.core.load_resource", "modulename": "bioimageio.core", "qualname": "load_resource", "kind": "function", "doc": "

load a bioimage.io resource description

\n\n

Args:\n source: Path or URL to an rdf.yaml or a bioimage.io package\n (zip-file with rdf.yaml in it).\n format_version: (optional) Use this argument to load the resource and\n convert its metadata to a higher format_version.\n perform_io_checks: Wether or not to perform validation that requires file io,\n e.g. downloading a remote files. The existence of local\n absolute file paths is still being checked.\n known_files: Allows to bypass download and hashing of referenced files\n (even if perform_io_checks is True).

\n\n

Returns:\n An object holding all metadata of the bioimage.io resource

\n", "signature": "(\tsource: Union[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]],\t/,\t*,\tformat_version: Union[Literal['discover'], Literal['latest'], str] = 'discover',\tperform_io_checks: bool = True,\tknown_files: Optional[Dict[str, bioimageio.spec._internal.io_basics.Sha256]] = None) -> Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.spec._internal.common_nodes.InvalidDescr]:", "funcdef": "def"}, "bioimageio.core.load_model": {"fullname": "bioimageio.core.load_model", "modulename": "bioimageio.core", "qualname": "load_model", "kind": "function", "doc": "

same as load_description, but addtionally ensures that the loaded\ndescription is valid and of type 'model'.

\n", "signature": "(\tsource: Union[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]],\t/,\t*,\tformat_version: Union[Literal['discover'], Literal['latest'], str] = 'discover',\tperform_io_checks: bool = True,\tknown_files: Optional[Dict[str, bioimageio.spec._internal.io_basics.Sha256]] = None) -> Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]:", "funcdef": "def"}, "bioimageio.core.axis": {"fullname": "bioimageio.core.axis", "modulename": "bioimageio.core.axis", "kind": "module", "doc": "

\n"}, "bioimageio.core.axis.AxisId": {"fullname": "bioimageio.core.axis.AxisId", "modulename": "bioimageio.core.axis", "qualname": "AxisId", "kind": "class", "doc": "

str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str

\n\n

Create a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to sys.getdefaultencoding().\nerrors defaults to 'strict'.

\n", "bases": "bioimageio.spec._internal.types.LowerCaseIdentifier"}, "bioimageio.core.axis.AxisId.root_model": {"fullname": "bioimageio.core.axis.AxisId.root_model", "modulename": "bioimageio.core.axis", "qualname": "AxisId.root_model", "kind": "variable", "doc": "

the pydantic root model to validate the string

\n", "annotation": ": ClassVar[Type[pydantic.root_model.RootModel[Any]]]", "default_value": "<class 'pydantic.root_model.RootModel[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]'>"}, "bioimageio.core.axis.PerAxis": {"fullname": "bioimageio.core.axis.PerAxis", "modulename": "bioimageio.core.axis", "qualname": "PerAxis", "kind": "variable", "doc": "

\n", "default_value": "typing.Mapping[bioimageio.spec.model.v0_5.AxisId, ~T]"}, "bioimageio.core.axis.BatchSize": {"fullname": "bioimageio.core.axis.BatchSize", "modulename": "bioimageio.core.axis", "qualname": "BatchSize", "kind": "variable", "doc": "

\n", "default_value": "<class 'int'>"}, "bioimageio.core.axis.AxisLetter": {"fullname": "bioimageio.core.axis.AxisLetter", "modulename": "bioimageio.core.axis", "qualname": "AxisLetter", "kind": "variable", "doc": "

\n", "default_value": "typing.Literal['b', 'i', 't', 'c', 'z', 'y', 'x']"}, "bioimageio.core.axis.AxisLike": {"fullname": "bioimageio.core.axis.AxisLike", "modulename": "bioimageio.core.axis", "qualname": "AxisLike", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bioimageio.spec.model.v0_5.AxisId, typing.Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, typing.Annotated[typing.Union[typing.Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], typing.Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[typing.Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], typing.Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], ForwardRef('Axis')]"}, "bioimageio.core.axis.Axis": {"fullname": "bioimageio.core.axis.Axis", "modulename": "bioimageio.core.axis", "qualname": "Axis", "kind": "class", "doc": "

\n"}, "bioimageio.core.axis.Axis.__init__": {"fullname": "bioimageio.core.axis.Axis.__init__", "modulename": "bioimageio.core.axis", "qualname": "Axis.__init__", "kind": "function", "doc": "

\n", "signature": "(\tid: bioimageio.spec.model.v0_5.AxisId,\ttype: Literal['batch', 'channel', 'index', 'space', 'time'])"}, "bioimageio.core.axis.Axis.id": {"fullname": "bioimageio.core.axis.Axis.id", "modulename": "bioimageio.core.axis", "qualname": "Axis.id", "kind": "variable", "doc": "

\n", "annotation": ": bioimageio.spec.model.v0_5.AxisId"}, "bioimageio.core.axis.Axis.type": {"fullname": "bioimageio.core.axis.Axis.type", "modulename": "bioimageio.core.axis", "qualname": "Axis.type", "kind": "variable", "doc": "

\n", "annotation": ": Literal['batch', 'channel', 'index', 'space', 'time']"}, "bioimageio.core.axis.Axis.create": {"fullname": "bioimageio.core.axis.Axis.create", "modulename": "bioimageio.core.axis", "qualname": "Axis.create", "kind": "function", "doc": "

\n", "signature": "(\tcls,\taxis: Union[bioimageio.spec.model.v0_5.AxisId, Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis]) -> bioimageio.core.axis.Axis:", "funcdef": "def"}, "bioimageio.core.axis.AxisInfo": {"fullname": "bioimageio.core.axis.AxisInfo", "modulename": "bioimageio.core.axis", "qualname": "AxisInfo", "kind": "class", "doc": "

\n", "bases": "Axis"}, "bioimageio.core.axis.AxisInfo.__init__": {"fullname": "bioimageio.core.axis.AxisInfo.__init__", "modulename": "bioimageio.core.axis", "qualname": "AxisInfo.__init__", "kind": "function", "doc": "

\n", "signature": "(\tid: bioimageio.spec.model.v0_5.AxisId,\ttype: Literal['batch', 'channel', 'index', 'space', 'time'],\tmaybe_singleton: bool)"}, "bioimageio.core.axis.AxisInfo.maybe_singleton": {"fullname": "bioimageio.core.axis.AxisInfo.maybe_singleton", "modulename": "bioimageio.core.axis", "qualname": "AxisInfo.maybe_singleton", "kind": "variable", "doc": "

\n", "annotation": ": bool"}, "bioimageio.core.axis.AxisInfo.create": {"fullname": "bioimageio.core.axis.AxisInfo.create", "modulename": "bioimageio.core.axis", "qualname": "AxisInfo.create", "kind": "function", "doc": "

\n", "signature": "(\tcls,\taxis: Union[bioimageio.spec.model.v0_5.AxisId, Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis],\tmaybe_singleton: Optional[bool] = None) -> bioimageio.core.axis.AxisInfo:", "funcdef": "def"}, "bioimageio.core.block": {"fullname": "bioimageio.core.block", "modulename": "bioimageio.core.block", "kind": "module", "doc": "

\n"}, "bioimageio.core.block.Block": {"fullname": "bioimageio.core.block.Block", "modulename": "bioimageio.core.block", "qualname": "Block", "kind": "class", "doc": "

A block/tile of a (larger) tensor

\n", "bases": "bioimageio.core.block_meta.BlockMeta"}, "bioimageio.core.block.Block.__init__": {"fullname": "bioimageio.core.block.Block.__init__", "modulename": "bioimageio.core.block", "qualname": "Block.__init__", "kind": "function", "doc": "

\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\tinner_slice: Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.SliceInfo],\thalo: Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.Halo],\tblock_index: int,\tblocks_in_sample: int,\tdata: bioimageio.core.tensor.Tensor)"}, "bioimageio.core.block.Block.data": {"fullname": "bioimageio.core.block.Block.data", "modulename": "bioimageio.core.block", "qualname": "Block.data", "kind": "variable", "doc": "

the block's tensor, e.g. a (padded) slice of some larger, original tensor

\n", "annotation": ": bioimageio.core.tensor.Tensor"}, "bioimageio.core.block.Block.inner_data": {"fullname": "bioimageio.core.block.Block.inner_data", "modulename": "bioimageio.core.block", "qualname": "Block.inner_data", "kind": "variable", "doc": "

\n"}, "bioimageio.core.block.Block.from_sample_member": {"fullname": "bioimageio.core.block.Block.from_sample_member", "modulename": "bioimageio.core.block", "qualname": "Block.from_sample_member", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tsample_member: bioimageio.core.tensor.Tensor,\tblock: bioimageio.core.block_meta.BlockMeta,\t*,\tpad_mode: Literal['edge', 'reflect', 'symmetric']) -> Self:", "funcdef": "def"}, "bioimageio.core.block.Block.get_transformed": {"fullname": "bioimageio.core.block.Block.get_transformed", "modulename": "bioimageio.core.block", "qualname": "Block.get_transformed", "kind": "function", "doc": "

\n", "signature": "(\tself,\tnew_axes: Mapping[bioimageio.spec.model.v0_5.AxisId, Union[bioimageio.core.block_meta.LinearAxisTransform, int]]) -> Self:", "funcdef": "def"}, "bioimageio.core.block.Block.from_meta": {"fullname": "bioimageio.core.block.Block.from_meta", "modulename": "bioimageio.core.block", "qualname": "Block.from_meta", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tmeta: bioimageio.core.block_meta.BlockMeta,\tdata: bioimageio.core.tensor.Tensor) -> Self:", "funcdef": "def"}, "bioimageio.core.block.split_tensor_into_blocks": {"fullname": "bioimageio.core.block.split_tensor_into_blocks", "modulename": "bioimageio.core.block", "qualname": "split_tensor_into_blocks", "kind": "function", "doc": "

divide a sample tensor into tensor blocks.

\n", "signature": "(\ttensor: bioimageio.core.tensor.Tensor,\tblock_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\t*,\thalo: Mapping[bioimageio.spec.model.v0_5.AxisId, Union[int, Tuple[int, int], bioimageio.core.common.Halo]],\tstride: Optional[Mapping[bioimageio.spec.model.v0_5.AxisId, int]] = None,\tpad_mode: Literal['edge', 'reflect', 'symmetric']) -> Tuple[int, Generator[bioimageio.core.block.Block, Any, NoneType]]:", "funcdef": "def"}, "bioimageio.core.block_meta": {"fullname": "bioimageio.core.block_meta", "modulename": "bioimageio.core.block_meta", "kind": "module", "doc": "

\n"}, "bioimageio.core.block_meta.LinearAxisTransform": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform", "kind": "class", "doc": "

\n"}, "bioimageio.core.block_meta.LinearAxisTransform.__init__": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform.__init__", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform.__init__", "kind": "function", "doc": "

\n", "signature": "(axis: bioimageio.spec.model.v0_5.AxisId, scale: float, offset: int)"}, "bioimageio.core.block_meta.LinearAxisTransform.axis": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform.axis", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform.axis", "kind": "variable", "doc": "

\n", "annotation": ": bioimageio.spec.model.v0_5.AxisId"}, "bioimageio.core.block_meta.LinearAxisTransform.scale": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform.scale", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform.scale", "kind": "variable", "doc": "

\n", "annotation": ": float"}, "bioimageio.core.block_meta.LinearAxisTransform.offset": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform.offset", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform.offset", "kind": "variable", "doc": "

\n", "annotation": ": int"}, "bioimageio.core.block_meta.LinearAxisTransform.compute": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform.compute", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform.compute", "kind": "function", "doc": "

\n", "signature": "(\tself,\ts: int,\tround: Callable[[float], int] = <built-in function floor>) -> int:", "funcdef": "def"}, "bioimageio.core.block_meta.BlockMeta": {"fullname": "bioimageio.core.block_meta.BlockMeta", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta", "kind": "class", "doc": "

Block meta data of a sample member (a tensor in a sample)

\n\n

Figure for illustration:\nThe first 2d block (dashed) of a sample member (bold).\nThe inner slice (thin) is expanded by a halo in both dimensions on both sides.\nThe outer slice reaches from the sample member origin (0, 0) to the right halo point.

\n\n
\u250c \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500  \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2510\n\u2577 halo(left)                         \u2577\n\u2577                                    \u2577\n\u2577  (0, 0)\u250f\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u252f\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u252f\u2501\u2501\u2501\u2794\n\u2577        \u2503                 \u2502         \u2577  sample member\n\u2577        \u2503      inner      \u2502         \u2577\n\u2577        \u2503   (and outer)   \u2502  outer  \u2577\n\u2577        \u2503      slice      \u2502  slice  \u2577\n\u2577        \u2503                 \u2502         \u2577\n\u2577        \u2523\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518         \u2577\n\u2577        \u2503   outer slice             \u2577\n\u2577        \u2503               halo(right) \u2577\n\u2514 \u2500 \u2500 \u2500 \u2500\u2503\u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500\u2518\n         \u2b07\n
\n\n

note:

\n\n
    \n
  • Inner and outer slices are specified in sample member coordinates.
    • \n
  • The outer_slice of a block at the sample edge may overlap by more than the\nhalo with the neighboring block (the inner slices will not overlap though).
    • \n
\n"}, "bioimageio.core.block_meta.BlockMeta.__init__": {"fullname": "bioimageio.core.block_meta.BlockMeta.__init__", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.__init__", "kind": "function", "doc": "

\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\tinner_slice: Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.SliceInfo],\thalo: Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.Halo],\tblock_index: int,\tblocks_in_sample: int)"}, "bioimageio.core.block_meta.BlockMeta.sample_shape": {"fullname": "bioimageio.core.block_meta.BlockMeta.sample_shape", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.sample_shape", "kind": "variable", "doc": "

the axis sizes of the whole (unblocked) sample

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, int]"}, "bioimageio.core.block_meta.BlockMeta.inner_slice": {"fullname": "bioimageio.core.block_meta.BlockMeta.inner_slice", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.inner_slice", "kind": "variable", "doc": "

inner region (without halo) wrt the sample

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.SliceInfo]"}, "bioimageio.core.block_meta.BlockMeta.halo": {"fullname": "bioimageio.core.block_meta.BlockMeta.halo", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.halo", "kind": "variable", "doc": "

halo enlarging the inner region to the block's sizes

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.Halo]"}, "bioimageio.core.block_meta.BlockMeta.block_index": {"fullname": "bioimageio.core.block_meta.BlockMeta.block_index", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.block_index", "kind": "variable", "doc": "

the i-th block of the sample

\n", "annotation": ": int"}, "bioimageio.core.block_meta.BlockMeta.blocks_in_sample": {"fullname": "bioimageio.core.block_meta.BlockMeta.blocks_in_sample", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.blocks_in_sample", "kind": "variable", "doc": "

total number of blocks in the sample

\n", "annotation": ": int"}, "bioimageio.core.block_meta.BlockMeta.shape": {"fullname": "bioimageio.core.block_meta.BlockMeta.shape", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.shape", "kind": "variable", "doc": "

axis lengths of the block

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, int]"}, "bioimageio.core.block_meta.BlockMeta.padding": {"fullname": "bioimageio.core.block_meta.BlockMeta.padding", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.padding", "kind": "variable", "doc": "

padding to realize the halo at the sample edge\nwhere we cannot simply enlarge the inner slice

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.PadWidth]"}, "bioimageio.core.block_meta.BlockMeta.outer_slice": {"fullname": "bioimageio.core.block_meta.BlockMeta.outer_slice", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.outer_slice", "kind": "variable", "doc": "

slice of the outer block (without padding) wrt the sample

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.SliceInfo]"}, "bioimageio.core.block_meta.BlockMeta.inner_shape": {"fullname": "bioimageio.core.block_meta.BlockMeta.inner_shape", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.inner_shape", "kind": "variable", "doc": "

axis lengths of the inner region (without halo)

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, int]"}, "bioimageio.core.block_meta.BlockMeta.local_slice": {"fullname": "bioimageio.core.block_meta.BlockMeta.local_slice", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.local_slice", "kind": "variable", "doc": "

inner slice wrt the block, not the sample

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.SliceInfo]"}, "bioimageio.core.block_meta.BlockMeta.dims": {"fullname": "bioimageio.core.block_meta.BlockMeta.dims", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.dims", "kind": "variable", "doc": "

\n", "annotation": ": Collection[bioimageio.spec.model.v0_5.AxisId]"}, "bioimageio.core.block_meta.BlockMeta.tagged_shape": {"fullname": "bioimageio.core.block_meta.BlockMeta.tagged_shape", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.tagged_shape", "kind": "variable", "doc": "

alias for shape

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, int]"}, "bioimageio.core.block_meta.BlockMeta.inner_slice_wo_overlap": {"fullname": "bioimageio.core.block_meta.BlockMeta.inner_slice_wo_overlap", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.inner_slice_wo_overlap", "kind": "variable", "doc": "

subslice of the inner slice, such that all inner_slice_wo_overlap can be\nstiched together trivially to form the original sample.

\n\n

This can also be used to calculate statistics\nwithout overrepresenting block edge regions.

\n"}, "bioimageio.core.block_meta.BlockMeta.get_transformed": {"fullname": "bioimageio.core.block_meta.BlockMeta.get_transformed", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.get_transformed", "kind": "function", "doc": "

\n", "signature": "(\tself,\tnew_axes: Mapping[bioimageio.spec.model.v0_5.AxisId, Union[bioimageio.core.block_meta.LinearAxisTransform, int]]) -> Self:", "funcdef": "def"}, "bioimageio.core.block_meta.split_shape_into_blocks": {"fullname": "bioimageio.core.block_meta.split_shape_into_blocks", "modulename": "bioimageio.core.block_meta", "qualname": "split_shape_into_blocks", "kind": "function", "doc": "

\n", "signature": "(\tshape: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\tblock_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\thalo: Mapping[bioimageio.spec.model.v0_5.AxisId, Union[int, Tuple[int, int], bioimageio.core.common.Halo]],\tstride: Optional[Mapping[bioimageio.spec.model.v0_5.AxisId, int]] = None) -> Tuple[int, Generator[bioimageio.core.block_meta.BlockMeta, Any, NoneType]]:", "funcdef": "def"}, "bioimageio.core.block_meta.split_multiple_shapes_into_blocks": {"fullname": "bioimageio.core.block_meta.split_multiple_shapes_into_blocks", "modulename": "bioimageio.core.block_meta", "qualname": "split_multiple_shapes_into_blocks", "kind": "function", "doc": "

\n", "signature": "(\tshapes: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tblock_shapes: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\t*,\thalo: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, Union[int, Tuple[int, int], bioimageio.core.common.Halo]]],\tstrides: Optional[Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]] = None,\tbroadcast: bool = False) -> Tuple[int, Iterable[Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.block_meta.BlockMeta]]]:", "funcdef": "def"}, "bioimageio.core.cli": {"fullname": "bioimageio.core.cli", "modulename": "bioimageio.core.cli", "kind": "module", "doc": "

bioimageio CLI

\n\n

Note: Some docstrings use a hair space '\u200a'\n to place the added '(default: ...)' on a new line.

\n"}, "bioimageio.core.cli.yaml": {"fullname": "bioimageio.core.cli.yaml", "modulename": "bioimageio.core.cli", "qualname": "yaml", "kind": "variable", "doc": "

\n", "default_value": "<ruyaml.main.YAML object>"}, "bioimageio.core.cli.CmdBase": {"fullname": "bioimageio.core.cli.CmdBase", "modulename": "bioimageio.core.cli", "qualname": "CmdBase", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.9/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of the class variables defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The synthesized __init__ [Signature][inspect.Signature] of the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The core schema of the model.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a [`RootModel`][pydantic.root_model.RootModel].\n__pydantic_serializer__: The `pydantic-core` `SchemaSerializer` used to dump instances of the model.\n__pydantic_validator__: The `pydantic-core` `SchemaValidator` used to validate instances of the model.\n\n__pydantic_extra__: A dictionary containing extra values, if [`extra`][pydantic.config.ConfigDict.extra]\n    is set to `'allow'`.\n__pydantic_fields_set__: The names of fields explicitly set during instantiation.\n__pydantic_private__: Values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "bioimageio.core.cli.CmdBase.model_config": {"fullname": "bioimageio.core.cli.CmdBase.model_config", "modulename": "bioimageio.core.cli", "qualname": "CmdBase.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'use_attribute_docstrings': True}"}, "bioimageio.core.cli.CmdBase.model_fields": {"fullname": "bioimageio.core.cli.CmdBase.model_fields", "modulename": "bioimageio.core.cli", "qualname": "CmdBase.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{}"}, "bioimageio.core.cli.CmdBase.model_computed_fields": {"fullname": "bioimageio.core.cli.CmdBase.model_computed_fields", "modulename": "bioimageio.core.cli", "qualname": "CmdBase.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.cli.ArgMixin": {"fullname": "bioimageio.core.cli.ArgMixin", "modulename": "bioimageio.core.cli", "qualname": "ArgMixin", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.9/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of the class variables defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The synthesized __init__ [Signature][inspect.Signature] of the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The core schema of the model.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a [`RootModel`][pydantic.root_model.RootModel].\n__pydantic_serializer__: The `pydantic-core` `SchemaSerializer` used to dump instances of the model.\n__pydantic_validator__: The `pydantic-core` `SchemaValidator` used to validate instances of the model.\n\n__pydantic_extra__: A dictionary containing extra values, if [`extra`][pydantic.config.ConfigDict.extra]\n    is set to `'allow'`.\n__pydantic_fields_set__: The names of fields explicitly set during instantiation.\n__pydantic_private__: Values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "bioimageio.core.cli.ArgMixin.model_config": {"fullname": "bioimageio.core.cli.ArgMixin.model_config", "modulename": "bioimageio.core.cli", "qualname": "ArgMixin.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'use_attribute_docstrings': True}"}, "bioimageio.core.cli.ArgMixin.model_fields": {"fullname": "bioimageio.core.cli.ArgMixin.model_fields", "modulename": "bioimageio.core.cli", "qualname": "ArgMixin.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{}"}, "bioimageio.core.cli.ArgMixin.model_computed_fields": {"fullname": "bioimageio.core.cli.ArgMixin.model_computed_fields", "modulename": "bioimageio.core.cli", "qualname": "ArgMixin.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.cli.WithSource": {"fullname": "bioimageio.core.cli.WithSource", "modulename": "bioimageio.core.cli", "qualname": "WithSource", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.9/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of the class variables defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The synthesized __init__ [Signature][inspect.Signature] of the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The core schema of the model.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a [`RootModel`][pydantic.root_model.RootModel].\n__pydantic_serializer__: The `pydantic-core` `SchemaSerializer` used to dump instances of the model.\n__pydantic_validator__: The `pydantic-core` `SchemaValidator` used to validate instances of the model.\n\n__pydantic_extra__: A dictionary containing extra values, if [`extra`][pydantic.config.ConfigDict.extra]\n    is set to `'allow'`.\n__pydantic_fields_set__: The names of fields explicitly set during instantiation.\n__pydantic_private__: Values of private attributes set on the model instance.\n
\n", "bases": "ArgMixin"}, "bioimageio.core.cli.WithSource.source": {"fullname": "bioimageio.core.cli.WithSource.source", "modulename": "bioimageio.core.cli", "qualname": "WithSource.source", "kind": "variable", "doc": "

Url/path to a bioimageio.yaml/rdf.yaml file\nor a bioimage.io resource identifier, e.g. 'affable-shark'

\n", "annotation": ": Annotated[str, <class 'pydantic_settings.sources._CliPositionalArg'>]"}, "bioimageio.core.cli.WithSource.descr": {"fullname": "bioimageio.core.cli.WithSource.descr", "modulename": "bioimageio.core.cli", "qualname": "WithSource.descr", "kind": "variable", "doc": "

\n"}, "bioimageio.core.cli.WithSource.descr_id": {"fullname": "bioimageio.core.cli.WithSource.descr_id", "modulename": "bioimageio.core.cli", "qualname": "WithSource.descr_id", "kind": "variable", "doc": "

a more user-friendly description id\n(replacing legacy ids with their nicknames)

\n", "annotation": ": str"}, "bioimageio.core.cli.WithSource.model_config": {"fullname": "bioimageio.core.cli.WithSource.model_config", "modulename": "bioimageio.core.cli", "qualname": "WithSource.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'use_attribute_docstrings': True}"}, "bioimageio.core.cli.WithSource.model_fields": {"fullname": "bioimageio.core.cli.WithSource.model_fields", "modulename": "bioimageio.core.cli", "qualname": "WithSource.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'source': FieldInfo(annotation=str, required=True, description="Url/path to a bioimageio.yaml/rdf.yaml file\\nor a bioimage.io resource identifier, e.g. 'affable-shark'", metadata=[<class 'pydantic_settings.sources._CliPositionalArg'>])}"}, "bioimageio.core.cli.WithSource.model_computed_fields": {"fullname": "bioimageio.core.cli.WithSource.model_computed_fields", "modulename": "bioimageio.core.cli", "qualname": "WithSource.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.cli.ValidateFormatCmd": {"fullname": "bioimageio.core.cli.ValidateFormatCmd", "modulename": "bioimageio.core.cli", "qualname": "ValidateFormatCmd", "kind": "class", "doc": "

bioimageio-validate-format - validate the meta data format of a bioimageio resource.

\n", "bases": "CmdBase, WithSource"}, "bioimageio.core.cli.ValidateFormatCmd.run": {"fullname": "bioimageio.core.cli.ValidateFormatCmd.run", "modulename": "bioimageio.core.cli", "qualname": "ValidateFormatCmd.run", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.cli.ValidateFormatCmd.model_config": {"fullname": "bioimageio.core.cli.ValidateFormatCmd.model_config", "modulename": "bioimageio.core.cli", "qualname": "ValidateFormatCmd.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'use_attribute_docstrings': True}"}, "bioimageio.core.cli.ValidateFormatCmd.model_fields": {"fullname": "bioimageio.core.cli.ValidateFormatCmd.model_fields", "modulename": "bioimageio.core.cli", "qualname": "ValidateFormatCmd.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'source': FieldInfo(annotation=str, required=True, description="Url/path to a bioimageio.yaml/rdf.yaml file\\nor a bioimage.io resource identifier, e.g. 'affable-shark'", metadata=[<class 'pydantic_settings.sources._CliPositionalArg'>])}"}, "bioimageio.core.cli.ValidateFormatCmd.model_computed_fields": {"fullname": "bioimageio.core.cli.ValidateFormatCmd.model_computed_fields", "modulename": "bioimageio.core.cli", "qualname": "ValidateFormatCmd.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.cli.TestCmd": {"fullname": "bioimageio.core.cli.TestCmd", "modulename": "bioimageio.core.cli", "qualname": "TestCmd", "kind": "class", "doc": "

bioimageio-test - Test a bioimageio resource (beyond meta data formatting)

\n", "bases": "CmdBase, WithSource"}, "bioimageio.core.cli.TestCmd.weight_format": {"fullname": "bioimageio.core.cli.TestCmd.weight_format", "modulename": "bioimageio.core.cli", "qualname": "TestCmd.weight_format", "kind": "variable", "doc": "

The weight format to limit testing to.

\n\n

(only relevant for model resources)

\n", "annotation": ": Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript', 'all']"}, "bioimageio.core.cli.TestCmd.devices": {"fullname": "bioimageio.core.cli.TestCmd.devices", "modulename": "bioimageio.core.cli", "qualname": "TestCmd.devices", "kind": "variable", "doc": "

Device(s) to use for testing

\n", "annotation": ": Union[str, Sequence[str], NoneType]"}, "bioimageio.core.cli.TestCmd.decimal": {"fullname": "bioimageio.core.cli.TestCmd.decimal", "modulename": "bioimageio.core.cli", "qualname": "TestCmd.decimal", "kind": "variable", "doc": "

Precision for numerical comparisons

\n", "annotation": ": int"}, "bioimageio.core.cli.TestCmd.run": {"fullname": "bioimageio.core.cli.TestCmd.run", "modulename": "bioimageio.core.cli", "qualname": "TestCmd.run", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.cli.TestCmd.model_config": {"fullname": "bioimageio.core.cli.TestCmd.model_config", "modulename": "bioimageio.core.cli", "qualname": "TestCmd.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'use_attribute_docstrings': True}"}, "bioimageio.core.cli.TestCmd.model_fields": {"fullname": "bioimageio.core.cli.TestCmd.model_fields", "modulename": "bioimageio.core.cli", "qualname": "TestCmd.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'source': FieldInfo(annotation=str, required=True, description="Url/path to a bioimageio.yaml/rdf.yaml file\\nor a bioimage.io resource identifier, e.g. 'affable-shark'", metadata=[<class 'pydantic_settings.sources._CliPositionalArg'>]), 'weight_format': FieldInfo(annotation=Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript', 'all'], required=False, default='all', description='The weight format to limit testing to.\\n\\n(only relevant for model resources)'), 'devices': FieldInfo(annotation=Union[str, Sequence[str], NoneType], required=False, default=None, description='Device(s) to use for testing'), 'decimal': FieldInfo(annotation=int, required=False, default=4, description='Precision for numerical comparisons')}"}, "bioimageio.core.cli.TestCmd.model_computed_fields": {"fullname": "bioimageio.core.cli.TestCmd.model_computed_fields", "modulename": "bioimageio.core.cli", "qualname": "TestCmd.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.cli.PackageCmd": {"fullname": "bioimageio.core.cli.PackageCmd", "modulename": "bioimageio.core.cli", "qualname": "PackageCmd", "kind": "class", "doc": "

bioimageio-package - save a resource's metadata with its associated files.

\n", "bases": "CmdBase, WithSource"}, "bioimageio.core.cli.PackageCmd.path": {"fullname": "bioimageio.core.cli.PackageCmd.path", "modulename": "bioimageio.core.cli", "qualname": "PackageCmd.path", "kind": "variable", "doc": "

The path to write the (zipped) package to.\nIf it does not have a .zip suffix\nthis command will save the package as an unzipped folder instead.

\n", "annotation": ": Annotated[pathlib.Path, <class 'pydantic_settings.sources._CliPositionalArg'>]"}, "bioimageio.core.cli.PackageCmd.weight_format": {"fullname": "bioimageio.core.cli.PackageCmd.weight_format", "modulename": "bioimageio.core.cli", "qualname": "PackageCmd.weight_format", "kind": "variable", "doc": "

The weight format to include in the package (for model descriptions only).

\n", "annotation": ": Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript', 'all']"}, "bioimageio.core.cli.PackageCmd.run": {"fullname": "bioimageio.core.cli.PackageCmd.run", "modulename": "bioimageio.core.cli", "qualname": "PackageCmd.run", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.cli.PackageCmd.model_config": {"fullname": "bioimageio.core.cli.PackageCmd.model_config", "modulename": "bioimageio.core.cli", "qualname": "PackageCmd.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'use_attribute_docstrings': True}"}, "bioimageio.core.cli.PackageCmd.model_fields": {"fullname": "bioimageio.core.cli.PackageCmd.model_fields", "modulename": "bioimageio.core.cli", "qualname": "PackageCmd.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'source': FieldInfo(annotation=str, required=True, description="Url/path to a bioimageio.yaml/rdf.yaml file\\nor a bioimage.io resource identifier, e.g. 'affable-shark'", metadata=[<class 'pydantic_settings.sources._CliPositionalArg'>]), 'path': FieldInfo(annotation=Path, required=True, description='The path to write the (zipped) package to.\\nIf it does not have a `.zip` suffix\\nthis command will save the package as an unzipped folder instead.', metadata=[<class 'pydantic_settings.sources._CliPositionalArg'>]), 'weight_format': FieldInfo(annotation=Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript', 'all'], required=False, default='all', description='The weight format to include in the package (for model descriptions only).')}"}, "bioimageio.core.cli.PackageCmd.model_computed_fields": {"fullname": "bioimageio.core.cli.PackageCmd.model_computed_fields", "modulename": "bioimageio.core.cli", "qualname": "PackageCmd.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.cli.PredictCmd": {"fullname": "bioimageio.core.cli.PredictCmd", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd", "kind": "class", "doc": "

bioimageio-predict - Run inference on your data with a bioimage.io model.

\n", "bases": "CmdBase, WithSource"}, "bioimageio.core.cli.PredictCmd.inputs": {"fullname": "bioimageio.core.cli.PredictCmd.inputs", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.inputs", "kind": "variable", "doc": "

Model input sample paths (for each input tensor)

\n\n

The input paths are expected to have shape...

\n\n
    \n
  • (n_samples,) or (n_samples,1) for models expecting a single input tensor
    • \n
  • (n_samples,) containing the substring '{input_id}', or
    • \n
  • (n_samples, n_model_inputs) to provide each input tensor path explicitly.
    • \n
\n\n

All substrings that are replaced by metadata from the model description:

\n\n
    \n
  • '{model_id}'
    • \n
  • '{input_id}'
    • \n
\n\n

Example inputs to process sample 'a' and 'b'\nfor a model expecting a 'raw' and a 'mask' input tensor:\n--inputs=\"[[\"a_raw.tif\",\"a_mask.tif\"],[\"b_raw.tif\",\"b_mask.tif\"]]\"\n(Note that JSON double quotes need to be escaped.)

\n\n

Alternatively a bioimageio-cli.yaml (or bioimageio-cli.json) file\nmay provide the arguments, e.g.:

\n\n
\n
inputs:\n- [a_raw.tif, a_mask.tif]\n- [b_raw.tif, b_mask.tif]\n
\n
\n\n

.npy and any file extension supported by imageio are supported.\n Aavailable formats are listed at\nhttps://imageio.readthedocs.io/en/stable/formats/index.html#all-formats.\nSome formats have additional dependencies.

\n", "annotation": ": Annotated[Sequence[Union[str, Annotated[Tuple[str, ...], MinLen(min_length=1)]]], MinLen(min_length=1)]"}, "bioimageio.core.cli.PredictCmd.outputs": {"fullname": "bioimageio.core.cli.PredictCmd.outputs", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.outputs", "kind": "variable", "doc": "

Model output path pattern (per output tensor)

\n\n

All substrings that are replaced:

\n\n
    \n
  • '{model_id}' (from model description)
    • \n
  • '{output_id}' (from model description)
    • \n
  • '{sample_id}' (extracted from input paths)
    • \n
\n", "annotation": ": Union[str, Annotated[Tuple[str, ...], MinLen(min_length=1)]]"}, "bioimageio.core.cli.PredictCmd.overwrite": {"fullname": "bioimageio.core.cli.PredictCmd.overwrite", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.overwrite", "kind": "variable", "doc": "

allow overwriting existing output files

\n", "annotation": ": bool"}, "bioimageio.core.cli.PredictCmd.blockwise": {"fullname": "bioimageio.core.cli.PredictCmd.blockwise", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.blockwise", "kind": "variable", "doc": "

process inputs blockwise

\n", "annotation": ": bool"}, "bioimageio.core.cli.PredictCmd.stats": {"fullname": "bioimageio.core.cli.PredictCmd.stats", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.stats", "kind": "variable", "doc": "

path to dataset statistics\n(will be written if it does not exist,\nbut the model requires statistical dataset measures)

\n", "annotation": ": pathlib.Path"}, "bioimageio.core.cli.PredictCmd.preview": {"fullname": "bioimageio.core.cli.PredictCmd.preview", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.preview", "kind": "variable", "doc": "

preview which files would be processed\nand what outputs would be generated.

\n", "annotation": ": bool"}, "bioimageio.core.cli.PredictCmd.weight_format": {"fullname": "bioimageio.core.cli.PredictCmd.weight_format", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.weight_format", "kind": "variable", "doc": "

The weight format to use.

\n", "annotation": ": Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript', 'any']"}, "bioimageio.core.cli.PredictCmd.example": {"fullname": "bioimageio.core.cli.PredictCmd.example", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.example", "kind": "variable", "doc": "

generate and run an example

\n\n
    \n
  1. downloads example model inputs
    2. \n
  2. creates a {model_id}_example folder
    3. \n
  3. writes input arguments to {model_id}_example/bioimageio-cli.yaml
    4. \n
  4. executes a preview dry-run
    5. \n
  5. executes prediction with example input
    6. \n
\n", "annotation": ": bool"}, "bioimageio.core.cli.PredictCmd.run": {"fullname": "bioimageio.core.cli.PredictCmd.run", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.run", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.cli.PredictCmd.model_config": {"fullname": "bioimageio.core.cli.PredictCmd.model_config", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'use_attribute_docstrings': True}"}, "bioimageio.core.cli.PredictCmd.model_fields": {"fullname": "bioimageio.core.cli.PredictCmd.model_fields", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'source': FieldInfo(annotation=str, required=True, description="Url/path to a bioimageio.yaml/rdf.yaml file\\nor a bioimage.io resource identifier, e.g. 'affable-shark'", metadata=[<class 'pydantic_settings.sources._CliPositionalArg'>]), 'inputs': FieldInfo(annotation=Sequence[Union[str, Annotated[Tuple[str, ...], MinLen]]], required=False, default=('{input_id}/001.tif',), description='Model input sample paths (for each input tensor)\\n\\nThe input paths are expected to have shape...\\n - (n_samples,) or (n_samples,1) for models expecting a single input tensor\\n - (n_samples,) containing the substring \\'{input_id}\\', or\\n - (n_samples, n_model_inputs) to provide each input tensor path explicitly.\\n\\nAll substrings that are replaced by metadata from the model description:\\n- \\'{model_id}\\'\\n- \\'{input_id}\\'\\n\\nExample inputs to process sample \\'a\\' and \\'b\\'\\nfor a model expecting a \\'raw\\' and a \\'mask\\' input tensor:\\n--inputs="[["a_raw.tif","a_mask.tif"],["b_raw.tif","b_mask.tif"]]"\\n(Note that JSON double quotes need to be escaped.)\\n\\nAlternatively a `bioimageio-cli.yaml` (or `bioimageio-cli.json`) file\\nmay provide the arguments, e.g.:\\n```yaml\\ninputs:\\n- [a_raw.tif, a_mask.tif]\\n- [b_raw.tif, b_mask.tif]\\n```\\n\\n`.npy` and any file extension supported by imageio are supported.\\n Aavailable formats are listed at\\nhttps://imageio.readthedocs.io/en/stable/formats/index.html#all-formats.\\nSome formats have additional dependencies.\\n\\n\\u200a', metadata=[MinLen(min_length=1)]), 'outputs': FieldInfo(annotation=Union[str, Annotated[Tuple[str, ...], MinLen]], required=False, default='outputs_{model_id}/{output_id}/{sample_id}.tif', description="Model output path pattern (per output tensor)\\n\\nAll substrings that are replaced:\\n- '{model_id}' (from model description)\\n- '{output_id}' (from model description)\\n- '{sample_id}' (extracted from input paths)\\n\\n\\u200a"), 'overwrite': FieldInfo(annotation=bool, required=False, default=False, description='allow overwriting existing output files'), 'blockwise': FieldInfo(annotation=bool, required=False, default=False, description='process inputs blockwise'), 'stats': FieldInfo(annotation=Path, required=False, default=PosixPath('dataset_statistics.json'), description='path to dataset statistics\\n(will be written if it does not exist,\\nbut the model requires statistical dataset measures)\\n\\u200a'), 'preview': FieldInfo(annotation=bool, required=False, default=False, description='preview which files would be processed\\nand what outputs would be generated.'), 'weight_format': FieldInfo(annotation=Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript', 'any'], required=False, default='any', description='The weight format to use.'), 'example': FieldInfo(annotation=bool, required=False, default=False, description='generate and run an example\\n\\n1. downloads example model inputs\\n2. creates a `{model_id}_example` folder\\n3. writes input arguments to `{model_id}_example/bioimageio-cli.yaml`\\n4. executes a preview dry-run\\n5. executes prediction with example input\\n\\n\\u200a')}"}, "bioimageio.core.cli.PredictCmd.model_computed_fields": {"fullname": "bioimageio.core.cli.PredictCmd.model_computed_fields", "modulename": "bioimageio.core.cli", "qualname": "PredictCmd.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.cli.JSON_FILE": {"fullname": "bioimageio.core.cli.JSON_FILE", "modulename": "bioimageio.core.cli", "qualname": "JSON_FILE", "kind": "variable", "doc": "

\n", "default_value": "'bioimageio-cli.json'"}, "bioimageio.core.cli.YAML_FILE": {"fullname": "bioimageio.core.cli.YAML_FILE", "modulename": "bioimageio.core.cli", "qualname": "YAML_FILE", "kind": "variable", "doc": "

\n", "default_value": "'bioimageio-cli.yaml'"}, "bioimageio.core.cli.Bioimageio": {"fullname": "bioimageio.core.cli.Bioimageio", "modulename": "bioimageio.core.cli", "qualname": "Bioimageio", "kind": "class", "doc": "

bioimageio - CLI for bioimage.io resources \ud83e\udd92

\n\n

library versions:\n bioimageio.core 0.6.10\n bioimageio.spec 0.6.10

\n\n

spec format versions:\n model RDF 0.5.3\n dataset RDF 0.3.0\n notebook RDF 0.3.0

\n", "bases": "pydantic_settings.main.BaseSettings"}, "bioimageio.core.cli.Bioimageio.model_config": {"fullname": "bioimageio.core.cli.Bioimageio.model_config", "modulename": "bioimageio.core.cli", "qualname": "Bioimageio.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "default_value": "{'extra': 'forbid', 'arbitrary_types_allowed': True, 'validate_default': True, 'case_sensitive': False, 'env_prefix': '', 'nested_model_default_partial_update': False, 'env_file': None, 'env_file_encoding': None, 'env_ignore_empty': False, 'env_nested_delimiter': None, 'env_parse_none_str': None, 'env_parse_enums': None, 'cli_prog_name': 'bioimageio', 'cli_parse_args': True, 'cli_parse_none_str': None, 'cli_hide_none_type': False, 'cli_avoid_json': False, 'cli_enforce_required': False, 'cli_use_class_docs_for_groups': True, 'cli_exit_on_error': True, 'cli_prefix': '', 'cli_flag_prefix_char': '-', 'cli_implicit_flags': False, 'cli_ignore_unknown_args': False, 'json_file': 'bioimageio-cli.json', 'json_file_encoding': None, 'yaml_file': 'bioimageio-cli.yaml', 'yaml_file_encoding': None, 'toml_file': None, 'secrets_dir': None, 'protected_namespaces': ('model_', 'settings_'), 'use_attribute_docstrings': True}"}, "bioimageio.core.cli.Bioimageio.validate_format": {"fullname": "bioimageio.core.cli.Bioimageio.validate_format", "modulename": "bioimageio.core.cli", "qualname": "Bioimageio.validate_format", "kind": "variable", "doc": "

Check a resource's metadata format

\n", "annotation": ": Annotated[Optional[bioimageio.core.cli.ValidateFormatCmd], <class 'pydantic_settings.sources._CliSubCommand'>]"}, "bioimageio.core.cli.Bioimageio.test": {"fullname": "bioimageio.core.cli.Bioimageio.test", "modulename": "bioimageio.core.cli", "qualname": "Bioimageio.test", "kind": "variable", "doc": "

Test a bioimageio resource (beyond meta data formatting)

\n", "annotation": ": Annotated[Optional[bioimageio.core.cli.TestCmd], <class 'pydantic_settings.sources._CliSubCommand'>]"}, "bioimageio.core.cli.Bioimageio.package": {"fullname": "bioimageio.core.cli.Bioimageio.package", "modulename": "bioimageio.core.cli", "qualname": "Bioimageio.package", "kind": "variable", "doc": "

Package a resource

\n", "annotation": ": Annotated[Optional[bioimageio.core.cli.PackageCmd], <class 'pydantic_settings.sources._CliSubCommand'>]"}, "bioimageio.core.cli.Bioimageio.predict": {"fullname": "bioimageio.core.cli.Bioimageio.predict", "modulename": "bioimageio.core.cli", "qualname": "Bioimageio.predict", "kind": "variable", "doc": "

Predict with a model resource

\n", "annotation": ": Annotated[Optional[bioimageio.core.cli.PredictCmd], <class 'pydantic_settings.sources._CliSubCommand'>]"}, "bioimageio.core.cli.Bioimageio.settings_customise_sources": {"fullname": "bioimageio.core.cli.Bioimageio.settings_customise_sources", "modulename": "bioimageio.core.cli", "qualname": "Bioimageio.settings_customise_sources", "kind": "function", "doc": "

Define the sources and their order for loading the settings values.

\n\n

Args:\n settings_cls: The Settings class.\n init_settings: The InitSettingsSource instance.\n env_settings: The EnvSettingsSource instance.\n dotenv_settings: The DotEnvSettingsSource instance.\n file_secret_settings: The SecretsSettingsSource instance.

\n\n

Returns:\n A tuple containing the sources and their order for loading the settings values.

\n", "signature": "(\tcls,\tsettings_cls: Type[pydantic_settings.main.BaseSettings],\tinit_settings: pydantic_settings.sources.PydanticBaseSettingsSource,\tenv_settings: pydantic_settings.sources.PydanticBaseSettingsSource,\tdotenv_settings: pydantic_settings.sources.PydanticBaseSettingsSource,\tfile_secret_settings: pydantic_settings.sources.PydanticBaseSettingsSource) -> Tuple[pydantic_settings.sources.PydanticBaseSettingsSource, ...]:", "funcdef": "def"}, "bioimageio.core.cli.Bioimageio.run": {"fullname": "bioimageio.core.cli.Bioimageio.run", "modulename": "bioimageio.core.cli", "qualname": "Bioimageio.run", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.cli.Bioimageio.model_fields": {"fullname": "bioimageio.core.cli.Bioimageio.model_fields", "modulename": "bioimageio.core.cli", "qualname": "Bioimageio.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'validate_format': FieldInfo(annotation=Union[ValidateFormatCmd, NoneType], required=True, description="Check a resource's metadata format", metadata=[<class 'pydantic_settings.sources._CliSubCommand'>]), 'test': FieldInfo(annotation=Union[TestCmd, NoneType], required=True, description='Test a bioimageio resource (beyond meta data formatting)', metadata=[<class 'pydantic_settings.sources._CliSubCommand'>]), 'package': FieldInfo(annotation=Union[PackageCmd, NoneType], required=True, description='Package a resource', metadata=[<class 'pydantic_settings.sources._CliSubCommand'>]), 'predict': FieldInfo(annotation=Union[PredictCmd, NoneType], required=True, description='Predict with a model resource', metadata=[<class 'pydantic_settings.sources._CliSubCommand'>])}"}, "bioimageio.core.cli.Bioimageio.model_computed_fields": {"fullname": "bioimageio.core.cli.Bioimageio.model_computed_fields", "modulename": "bioimageio.core.cli", "qualname": "Bioimageio.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.commands": {"fullname": "bioimageio.core.commands", "modulename": "bioimageio.core.commands", "kind": "module", "doc": "

These functions implement the logic of the bioimageio command line interface\ndefined in the cli module.

\n"}, "bioimageio.core.commands.WeightFormatArgAll": {"fullname": "bioimageio.core.commands.WeightFormatArgAll", "modulename": "bioimageio.core.commands", "qualname": "WeightFormatArgAll", "kind": "variable", "doc": "

\n", "default_value": "typing.Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript', 'all']"}, "bioimageio.core.commands.WeightFormatArgAny": {"fullname": "bioimageio.core.commands.WeightFormatArgAny", "modulename": "bioimageio.core.commands", "qualname": "WeightFormatArgAny", "kind": "variable", "doc": "

\n", "default_value": "typing.Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript', 'any']"}, "bioimageio.core.commands.test": {"fullname": "bioimageio.core.commands.test", "modulename": "bioimageio.core.commands", "qualname": "test", "kind": "function", "doc": "

test a bioimageio resource

\n\n

Args:\n source: Path or URL to the bioimageio resource description file\n (bioimageio.yaml or rdf.yaml) or to a zipped resource\n weight_format: (model only) The weight format to use\n devices: Device(s) to use for testing\n decimal: Precision for numerical comparisons

\n", "signature": "(\tdescr: Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.spec._internal.common_nodes.InvalidDescr],\t*,\tweight_format: Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript', 'all'] = 'all',\tdevices: Union[str, Sequence[str], NoneType] = None,\tdecimal: int = 4):", "funcdef": "def"}, "bioimageio.core.commands.validate_format": {"fullname": "bioimageio.core.commands.validate_format", "modulename": "bioimageio.core.commands", "qualname": "validate_format", "kind": "function", "doc": "

validate the meta data format of a bioimageio resource

\n\n

Args:\n descr: a bioimageio resource description

\n", "signature": "(\tdescr: Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.spec._internal.common_nodes.InvalidDescr]):", "funcdef": "def"}, "bioimageio.core.commands.package": {"fullname": "bioimageio.core.commands.package", "modulename": "bioimageio.core.commands", "qualname": "package", "kind": "function", "doc": "

Save a resource's metadata with its associated files.

\n\n

Note: If path does not have a .zip suffix this command will save the\n package as an unzipped folder instead.

\n\n

Args:\n descr: a bioimageio resource description\n path: output path\n weight-format: include only this single weight-format (if not 'all').

\n", "signature": "(\tdescr: Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]],\tpath: pathlib.Path,\t*,\tweight_format: Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript', 'all'] = 'all'):", "funcdef": "def"}, "bioimageio.core.common": {"fullname": "bioimageio.core.common", "modulename": "bioimageio.core.common", "kind": "module", "doc": "

\n"}, "bioimageio.core.common.DTypeStr": {"fullname": "bioimageio.core.common.DTypeStr", "modulename": "bioimageio.core.common", "qualname": "DTypeStr", "kind": "variable", "doc": "

\n", "default_value": "typing.Literal['bool', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64']"}, "bioimageio.core.common.CropWidth": {"fullname": "bioimageio.core.common.CropWidth", "modulename": "bioimageio.core.common", "qualname": "CropWidth", "kind": "class", "doc": "

_LeftRight(left, right)

\n", "bases": "typing.NamedTuple"}, "bioimageio.core.common.CropWidth.__init__": {"fullname": "bioimageio.core.common.CropWidth.__init__", "modulename": "bioimageio.core.common", "qualname": "CropWidth.__init__", "kind": "function", "doc": "

Create new instance of _LeftRight(left, right)

\n", "signature": "(left: int, right: int)"}, "bioimageio.core.common.CropWidthLike": {"fullname": "bioimageio.core.common.CropWidthLike", "modulename": "bioimageio.core.common", "qualname": "CropWidthLike", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[int, typing.Tuple[int, int], bioimageio.core.common.CropWidth]"}, "bioimageio.core.common.CropWhere": {"fullname": "bioimageio.core.common.CropWhere", "modulename": "bioimageio.core.common", "qualname": "CropWhere", "kind": "variable", "doc": "

\n", "default_value": "typing.Literal['left', 'right', 'left_and_right']"}, "bioimageio.core.common.Halo": {"fullname": "bioimageio.core.common.Halo", "modulename": "bioimageio.core.common", "qualname": "Halo", "kind": "class", "doc": "

_LeftRight(left, right)

\n", "bases": "typing.NamedTuple"}, "bioimageio.core.common.Halo.__init__": {"fullname": "bioimageio.core.common.Halo.__init__", "modulename": "bioimageio.core.common", "qualname": "Halo.__init__", "kind": "function", "doc": "

Create new instance of _LeftRight(left, right)

\n", "signature": "(left: int, right: int)"}, "bioimageio.core.common.HaloLike": {"fullname": "bioimageio.core.common.HaloLike", "modulename": "bioimageio.core.common", "qualname": "HaloLike", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[int, typing.Tuple[int, int], bioimageio.core.common.Halo]"}, "bioimageio.core.common.OverlapWidth": {"fullname": "bioimageio.core.common.OverlapWidth", "modulename": "bioimageio.core.common", "qualname": "OverlapWidth", "kind": "class", "doc": "

_LeftRight(left, right)

\n", "bases": "typing.NamedTuple"}, "bioimageio.core.common.OverlapWidth.__init__": {"fullname": "bioimageio.core.common.OverlapWidth.__init__", "modulename": "bioimageio.core.common", "qualname": "OverlapWidth.__init__", "kind": "function", "doc": "

Create new instance of _LeftRight(left, right)

\n", "signature": "(left: int, right: int)"}, "bioimageio.core.common.PadWidth": {"fullname": "bioimageio.core.common.PadWidth", "modulename": "bioimageio.core.common", "qualname": "PadWidth", "kind": "class", "doc": "

_LeftRight(left, right)

\n", "bases": "typing.NamedTuple"}, "bioimageio.core.common.PadWidth.__init__": {"fullname": "bioimageio.core.common.PadWidth.__init__", "modulename": "bioimageio.core.common", "qualname": "PadWidth.__init__", "kind": "function", "doc": "

Create new instance of _LeftRight(left, right)

\n", "signature": "(left: int, right: int)"}, "bioimageio.core.common.PadWidthLike": {"fullname": "bioimageio.core.common.PadWidthLike", "modulename": "bioimageio.core.common", "qualname": "PadWidthLike", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[int, typing.Tuple[int, int], bioimageio.core.common.PadWidth]"}, "bioimageio.core.common.PadMode": {"fullname": "bioimageio.core.common.PadMode", "modulename": "bioimageio.core.common", "qualname": "PadMode", "kind": "variable", "doc": "

\n", "default_value": "typing.Literal['edge', 'reflect', 'symmetric']"}, "bioimageio.core.common.PadWhere": {"fullname": "bioimageio.core.common.PadWhere", "modulename": "bioimageio.core.common", "qualname": "PadWhere", "kind": "variable", "doc": "

\n", "default_value": "typing.Literal['left', 'right', 'left_and_right']"}, "bioimageio.core.common.SliceInfo": {"fullname": "bioimageio.core.common.SliceInfo", "modulename": "bioimageio.core.common", "qualname": "SliceInfo", "kind": "class", "doc": "

SliceInfo(start, stop)

\n", "bases": "typing.NamedTuple"}, "bioimageio.core.common.SliceInfo.__init__": {"fullname": "bioimageio.core.common.SliceInfo.__init__", "modulename": "bioimageio.core.common", "qualname": "SliceInfo.__init__", "kind": "function", "doc": "

Create new instance of SliceInfo(start, stop)

\n", "signature": "(start: int, stop: int)"}, "bioimageio.core.common.SliceInfo.start": {"fullname": "bioimageio.core.common.SliceInfo.start", "modulename": "bioimageio.core.common", "qualname": "SliceInfo.start", "kind": "variable", "doc": "

Alias for field number 0

\n", "annotation": ": int"}, "bioimageio.core.common.SliceInfo.stop": {"fullname": "bioimageio.core.common.SliceInfo.stop", "modulename": "bioimageio.core.common", "qualname": "SliceInfo.stop", "kind": "variable", "doc": "

Alias for field number 1

\n", "annotation": ": int"}, "bioimageio.core.common.SampleId": {"fullname": "bioimageio.core.common.SampleId", "modulename": "bioimageio.core.common", "qualname": "SampleId", "kind": "variable", "doc": "

\n", "default_value": "typing.Hashable"}, "bioimageio.core.common.MemberId": {"fullname": "bioimageio.core.common.MemberId", "modulename": "bioimageio.core.common", "qualname": "MemberId", "kind": "variable", "doc": "

\n", "default_value": "<class 'bioimageio.spec.model.v0_5.TensorId'>"}, "bioimageio.core.common.PerMember": {"fullname": "bioimageio.core.common.PerMember", "modulename": "bioimageio.core.common", "qualname": "PerMember", "kind": "variable", "doc": "

\n", "default_value": "typing.Mapping[bioimageio.spec.model.v0_5.TensorId, ~T]"}, "bioimageio.core.common.BlockIndex": {"fullname": "bioimageio.core.common.BlockIndex", "modulename": "bioimageio.core.common", "qualname": "BlockIndex", "kind": "variable", "doc": "

\n", "default_value": "<class 'int'>"}, "bioimageio.core.common.TotalNumberOfBlocks": {"fullname": "bioimageio.core.common.TotalNumberOfBlocks", "modulename": "bioimageio.core.common", "qualname": "TotalNumberOfBlocks", "kind": "variable", "doc": "

\n", "default_value": "<class 'int'>"}, "bioimageio.core.common.Frozen": {"fullname": "bioimageio.core.common.Frozen", "modulename": "bioimageio.core.common", "qualname": "Frozen", "kind": "variable", "doc": "

\n", "default_value": "<class 'mappingproxy'>"}, "bioimageio.core.dataset": {"fullname": "bioimageio.core.dataset", "modulename": "bioimageio.core.dataset", "kind": "module", "doc": "

\n"}, "bioimageio.core.dataset.Dataset": {"fullname": "bioimageio.core.dataset.Dataset", "modulename": "bioimageio.core.dataset", "qualname": "Dataset", "kind": "variable", "doc": "

\n", "default_value": "typing.Iterable[bioimageio.core.sample.Sample]"}, "bioimageio.core.digest_spec": {"fullname": "bioimageio.core.digest_spec", "modulename": "bioimageio.core.digest_spec", "kind": "module", "doc": "

\n"}, "bioimageio.core.digest_spec.import_callable": {"fullname": "bioimageio.core.digest_spec.import_callable", "modulename": "bioimageio.core.digest_spec", "qualname": "import_callable", "kind": "function", "doc": "

import a callable (e.g. a torch.nn.Module) from a spec node describing it

\n", "signature": "(\tnode: Union[bioimageio.spec.model.v0_4.CallableFromDepencency, bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr],\t/,\t**kwargs: Unpack[bioimageio.spec._internal.io.HashKwargs]) -> Callable[..., Any]:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_axes_infos": {"fullname": "bioimageio.core.digest_spec.get_axes_infos", "modulename": "bioimageio.core.digest_spec", "qualname": "get_axes_infos", "kind": "function", "doc": "

get a unified, simplified axis representation from spec axes

\n", "signature": "(\tio_descr: Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_4.OutputTensorDescr, bioimageio.spec.model.v0_5.InputTensorDescr, bioimageio.spec.model.v0_5.OutputTensorDescr]) -> List[bioimageio.core.axis.AxisInfo]:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_member_id": {"fullname": "bioimageio.core.digest_spec.get_member_id", "modulename": "bioimageio.core.digest_spec", "qualname": "get_member_id", "kind": "function", "doc": "

get the normalized tensor ID, usable as a sample member ID

\n", "signature": "(\ttensor_description: Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_4.OutputTensorDescr, bioimageio.spec.model.v0_5.InputTensorDescr, bioimageio.spec.model.v0_5.OutputTensorDescr]) -> bioimageio.spec.model.v0_5.TensorId:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_member_ids": {"fullname": "bioimageio.core.digest_spec.get_member_ids", "modulename": "bioimageio.core.digest_spec", "qualname": "get_member_ids", "kind": "function", "doc": "

get normalized tensor IDs to be used as sample member IDs

\n", "signature": "(\ttensor_descriptions: Sequence[Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_4.OutputTensorDescr, bioimageio.spec.model.v0_5.InputTensorDescr, bioimageio.spec.model.v0_5.OutputTensorDescr]]) -> List[bioimageio.spec.model.v0_5.TensorId]:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_test_inputs": {"fullname": "bioimageio.core.digest_spec.get_test_inputs", "modulename": "bioimageio.core.digest_spec", "qualname": "get_test_inputs", "kind": "function", "doc": "

returns a model's test input sample

\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]) -> bioimageio.core.sample.Sample:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_test_outputs": {"fullname": "bioimageio.core.digest_spec.get_test_outputs", "modulename": "bioimageio.core.digest_spec", "qualname": "get_test_outputs", "kind": "function", "doc": "

returns a model's test output sample

\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]) -> bioimageio.core.sample.Sample:", "funcdef": "def"}, "bioimageio.core.digest_spec.IO_SampleBlockMeta": {"fullname": "bioimageio.core.digest_spec.IO_SampleBlockMeta", "modulename": "bioimageio.core.digest_spec", "qualname": "IO_SampleBlockMeta", "kind": "class", "doc": "

IO_SampleBlockMeta(input, output)

\n", "bases": "typing.NamedTuple"}, "bioimageio.core.digest_spec.IO_SampleBlockMeta.__init__": {"fullname": "bioimageio.core.digest_spec.IO_SampleBlockMeta.__init__", "modulename": "bioimageio.core.digest_spec", "qualname": "IO_SampleBlockMeta.__init__", "kind": "function", "doc": "

Create new instance of IO_SampleBlockMeta(input, output)

\n", "signature": "(\tinput: ForwardRef('SampleBlockMeta'),\toutput: ForwardRef('SampleBlockMeta'))"}, "bioimageio.core.digest_spec.IO_SampleBlockMeta.input": {"fullname": "bioimageio.core.digest_spec.IO_SampleBlockMeta.input", "modulename": "bioimageio.core.digest_spec", "qualname": "IO_SampleBlockMeta.input", "kind": "variable", "doc": "

Alias for field number 0

\n", "annotation": ": bioimageio.core.sample.SampleBlockMeta"}, "bioimageio.core.digest_spec.IO_SampleBlockMeta.output": {"fullname": "bioimageio.core.digest_spec.IO_SampleBlockMeta.output", "modulename": "bioimageio.core.digest_spec", "qualname": "IO_SampleBlockMeta.output", "kind": "variable", "doc": "

Alias for field number 1

\n", "annotation": ": bioimageio.core.sample.SampleBlockMeta"}, "bioimageio.core.digest_spec.get_input_halo": {"fullname": "bioimageio.core.digest_spec.get_input_halo", "modulename": "bioimageio.core.digest_spec", "qualname": "get_input_halo", "kind": "function", "doc": "

returns which halo input tensors need to be divided into blocks with such that\noutput_halo can be cropped from their outputs without intorducing gaps.

\n", "signature": "(\tmodel: bioimageio.spec.model.v0_5.ModelDescr,\toutput_halo: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.Halo]]):", "funcdef": "def"}, "bioimageio.core.digest_spec.get_block_transform": {"fullname": "bioimageio.core.digest_spec.get_block_transform", "modulename": "bioimageio.core.digest_spec", "qualname": "get_block_transform", "kind": "function", "doc": "

returns how a model's output tensor shapes relate to its input shapes

\n", "signature": "(model: bioimageio.spec.model.v0_5.ModelDescr):", "funcdef": "def"}, "bioimageio.core.digest_spec.get_io_sample_block_metas": {"fullname": "bioimageio.core.digest_spec.get_io_sample_block_metas", "modulename": "bioimageio.core.digest_spec", "qualname": "get_io_sample_block_metas", "kind": "function", "doc": "

returns an iterable yielding meta data for corresponding input and output samples

\n", "signature": "(\tmodel: bioimageio.spec.model.v0_5.ModelDescr,\tinput_sample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tns: Mapping[Tuple[bioimageio.spec.model.v0_5.TensorId, bioimageio.spec.model.v0_5.AxisId], int],\tbatch_size: int = 1) -> Tuple[int, Iterable[bioimageio.core.digest_spec.IO_SampleBlockMeta]]:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_tensor": {"fullname": "bioimageio.core.digest_spec.get_tensor", "modulename": "bioimageio.core.digest_spec", "qualname": "get_tensor", "kind": "function", "doc": "

helper to cast/load various tensor sources

\n", "signature": "(\tsrc: Union[bioimageio.core.tensor.Tensor, xarray.core.dataarray.DataArray, numpy.ndarray[Any, numpy.dtype[Any]], pathlib.Path],\tipt: Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_5.InputTensorDescr]):", "funcdef": "def"}, "bioimageio.core.digest_spec.create_sample_for_model": {"fullname": "bioimageio.core.digest_spec.create_sample_for_model", "modulename": "bioimageio.core.digest_spec", "qualname": "create_sample_for_model", "kind": "function", "doc": "

Create a sample from a single set of input(s) for a specific bioimage.io model

\n\n

Args:\n model: a bioimage.io model description\n stat: dictionary with sample and dataset statistics (may be updated in-place!)\n inputs: the input(s) constituting a single sample.

\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)],\t*,\tstat: Optional[Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]]] = None,\tsample_id: Hashable = None,\tinputs: Optional[Mapping[bioimageio.spec.model.v0_5.TensorId, Union[bioimageio.core.tensor.Tensor, xarray.core.dataarray.DataArray, numpy.ndarray[Any, numpy.dtype[Any]], pathlib.Path]]] = None,\t**kwargs: numpy.ndarray[typing.Any, numpy.dtype[typing.Any]]) -> bioimageio.core.sample.Sample:", "funcdef": "def"}, "bioimageio.core.digest_spec.load_sample_for_model": {"fullname": "bioimageio.core.digest_spec.load_sample_for_model", "modulename": "bioimageio.core.digest_spec", "qualname": "load_sample_for_model", "kind": "function", "doc": "

load a single sample from paths that can be processed by model

\n", "signature": "(\t*,\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)],\tpaths: Mapping[bioimageio.spec.model.v0_5.TensorId, pathlib.Path],\taxes: Optional[Mapping[bioimageio.spec.model.v0_5.TensorId, Sequence[Union[bioimageio.spec.model.v0_5.AxisId, Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis]]]] = None,\tstat: Optional[Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]]] = None,\tsample_id: Optional[Hashable] = None):", "funcdef": "def"}, "bioimageio.core.io": {"fullname": "bioimageio.core.io", "modulename": "bioimageio.core.io", "kind": "module", "doc": "

\n"}, "bioimageio.core.io.load_image": {"fullname": "bioimageio.core.io.load_image", "modulename": "bioimageio.core.io", "qualname": "load_image", "kind": "function", "doc": "

load a single image as numpy array

\n\n

Args:\n path: image path\n is_volume: deprecated

\n", "signature": "(\tpath: pathlib.Path,\tis_volume: Optional[bool] = None) -> numpy.ndarray[typing.Any, numpy.dtype[typing.Any]]:", "funcdef": "def"}, "bioimageio.core.io.load_tensor": {"fullname": "bioimageio.core.io.load_tensor", "modulename": "bioimageio.core.io", "qualname": "load_tensor", "kind": "function", "doc": "

\n", "signature": "(\tpath: pathlib.Path,\taxes: Optional[Sequence[Union[bioimageio.spec.model.v0_5.AxisId, Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis]]] = None) -> bioimageio.core.tensor.Tensor:", "funcdef": "def"}, "bioimageio.core.io.save_tensor": {"fullname": "bioimageio.core.io.save_tensor", "modulename": "bioimageio.core.io", "qualname": "save_tensor", "kind": "function", "doc": "

\n", "signature": "(path: pathlib.Path, tensor: bioimageio.core.tensor.Tensor) -> None:", "funcdef": "def"}, "bioimageio.core.io.save_sample": {"fullname": "bioimageio.core.io.save_sample", "modulename": "bioimageio.core.io", "qualname": "save_sample", "kind": "function", "doc": "

save a sample to path

\n\n

If path is a pathlib.Path or a string it must contain {member_id} and may contain {sample_id},\nwhich are resolved with the sample object.

\n", "signature": "(\tpath: Union[pathlib.Path, str, Mapping[bioimageio.spec.model.v0_5.TensorId, pathlib.Path]],\tsample: bioimageio.core.sample.Sample) -> None:", "funcdef": "def"}, "bioimageio.core.io.save_dataset_stat": {"fullname": "bioimageio.core.io.save_dataset_stat", "modulename": "bioimageio.core.io", "qualname": "save_dataset_stat", "kind": "function", "doc": "

\n", "signature": "(\tstat: Mapping[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]],\tpath: pathlib.Path):", "funcdef": "def"}, "bioimageio.core.io.load_dataset_stat": {"fullname": "bioimageio.core.io.load_dataset_stat", "modulename": "bioimageio.core.io", "qualname": "load_dataset_stat", "kind": "function", "doc": "

\n", "signature": "(path: pathlib.Path):", "funcdef": "def"}, "bioimageio.core.model_adapters": {"fullname": "bioimageio.core.model_adapters", "modulename": "bioimageio.core.model_adapters", "kind": "module", "doc": "

\n"}, "bioimageio.core.prediction": {"fullname": "bioimageio.core.prediction", "modulename": "bioimageio.core.prediction", "kind": "module", "doc": "

\n"}, "bioimageio.core.prediction.predict": {"fullname": "bioimageio.core.prediction.predict", "modulename": "bioimageio.core.prediction", "qualname": "predict", "kind": "function", "doc": "

Run prediction for a single set of input(s) with a bioimage.io model

\n\n

Args:\n model: model to predict with.\n May be given as RDF source, model description or prediction pipeline.\n inputs: the input sample or the named input(s) for this model as a dictionary\n sample_id: the sample id.\n blocksize_parameter: (optional) tile the input into blocks parametrized by\n blocksize according to any parametrized axis sizes defined in the model RDF.\n Note: For a predetermined, fixed block shape use input_block_shape\n input_block_shape: (optional) tile the input sample tensors into blocks.\n Note: For a parameterized block shape, not dealing with the exact block shape,\n use blocksize_parameter.\n skip_preprocessing: flag to skip the model's preprocessing\n skip_postprocessing: flag to skip the model's postprocessing\n save_output_path: A path with {member_id} {sample_id} in it\n to save the output to.

\n", "signature": "(\t*,\tmodel: Union[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr, bioimageio.core._prediction_pipeline.PredictionPipeline],\tinputs: Union[bioimageio.core.sample.Sample, Mapping[bioimageio.spec.model.v0_5.TensorId, Union[bioimageio.core.tensor.Tensor, xarray.core.dataarray.DataArray, numpy.ndarray[Any, numpy.dtype[Any]], pathlib.Path]]],\tsample_id: Hashable = 'sample',\tblocksize_parameter: Union[int, Mapping[Tuple[bioimageio.spec.model.v0_5.TensorId, bioimageio.spec.model.v0_5.AxisId], int], NoneType] = None,\tinput_block_shape: Optional[Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]] = None,\tskip_preprocessing: bool = False,\tskip_postprocessing: bool = False,\tsave_output_path: Union[pathlib.Path, str, NoneType] = None) -> bioimageio.core.sample.Sample:", "funcdef": "def"}, "bioimageio.core.prediction.predict_many": {"fullname": "bioimageio.core.prediction.predict_many", "modulename": "bioimageio.core.prediction", "qualname": "predict_many", "kind": "function", "doc": "

Run prediction for a multiple sets of inputs with a bioimage.io model

\n\n

Args:\n model: model to predict with.\n May be given as RDF source, model description or prediction pipeline.\n inputs: An iterable of the named input(s) for this model as a dictionary.\n sample_id: the sample id.\n note: {i} will be formatted as the i-th sample.\n If {i} (or {i:) is not present and inputs is an iterable {i:03} is appended.\n blocksize_parameter: (optional) tile the input into blocks parametrized by\n blocksize according to any parametrized axis sizes defined in the model RDF\n skip_preprocessing: flag to skip the model's preprocessing\n skip_postprocessing: flag to skip the model's postprocessing\n save_output_path: A path with {member_id} {sample_id} in it\n to save the output to.

\n", "signature": "(\t*,\tmodel: Union[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr, bioimageio.core._prediction_pipeline.PredictionPipeline],\tinputs: Iterable[Mapping[bioimageio.spec.model.v0_5.TensorId, Union[bioimageio.core.tensor.Tensor, xarray.core.dataarray.DataArray, numpy.ndarray[Any, numpy.dtype[Any]], pathlib.Path]]],\tsample_id: str = 'sample{i:03}',\tblocksize_parameter: Union[int, Mapping[Tuple[bioimageio.spec.model.v0_5.TensorId, bioimageio.spec.model.v0_5.AxisId], int], NoneType] = None,\tskip_preprocessing: bool = False,\tskip_postprocessing: bool = False,\tsave_output_path: Union[pathlib.Path, str, NoneType] = None) -> Iterator[bioimageio.core.sample.Sample]:", "funcdef": "def"}, "bioimageio.core.proc_ops": {"fullname": "bioimageio.core.proc_ops", "modulename": "bioimageio.core.proc_ops", "kind": "module", "doc": "

\n"}, "bioimageio.core.proc_ops.AddKnownDatasetStats": {"fullname": "bioimageio.core.proc_ops.AddKnownDatasetStats", "modulename": "bioimageio.core.proc_ops", "qualname": "AddKnownDatasetStats", "kind": "class", "doc": "

\n", "bases": "bioimageio.core._op_base.BlockedOperator"}, "bioimageio.core.proc_ops.AddKnownDatasetStats.__init__": {"fullname": "bioimageio.core.proc_ops.AddKnownDatasetStats.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "AddKnownDatasetStats.__init__", "kind": "function", "doc": "

\n", "signature": "(\tdataset_stats: Mapping[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]])"}, "bioimageio.core.proc_ops.AddKnownDatasetStats.dataset_stats": {"fullname": "bioimageio.core.proc_ops.AddKnownDatasetStats.dataset_stats", "modulename": "bioimageio.core.proc_ops", "qualname": "AddKnownDatasetStats.dataset_stats", "kind": "variable", "doc": "

\n", "annotation": ": Mapping[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]"}, "bioimageio.core.proc_ops.AddKnownDatasetStats.required_measures": {"fullname": "bioimageio.core.proc_ops.AddKnownDatasetStats.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "AddKnownDatasetStats.required_measures", "kind": "variable", "doc": "

\n", "annotation": ": Set[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_ops.UpdateStats": {"fullname": "bioimageio.core.proc_ops.UpdateStats", "modulename": "bioimageio.core.proc_ops", "qualname": "UpdateStats", "kind": "class", "doc": "

Calculates sample and/or dataset measures

\n", "bases": "bioimageio.core._op_base.Operator"}, "bioimageio.core.proc_ops.UpdateStats.__init__": {"fullname": "bioimageio.core.proc_ops.UpdateStats.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "UpdateStats.__init__", "kind": "function", "doc": "

\n", "signature": "(\tstats_calculator: bioimageio.core.stat_calculators.StatsCalculator,\tkeep_updating_initial_dataset_stats: bool = False)"}, "bioimageio.core.proc_ops.UpdateStats.stats_calculator": {"fullname": "bioimageio.core.proc_ops.UpdateStats.stats_calculator", "modulename": "bioimageio.core.proc_ops", "qualname": "UpdateStats.stats_calculator", "kind": "variable", "doc": "

StatsCalculator to be used by this operator.

\n", "annotation": ": bioimageio.core.stat_calculators.StatsCalculator"}, "bioimageio.core.proc_ops.UpdateStats.keep_updating_initial_dataset_stats": {"fullname": "bioimageio.core.proc_ops.UpdateStats.keep_updating_initial_dataset_stats", "modulename": "bioimageio.core.proc_ops", "qualname": "UpdateStats.keep_updating_initial_dataset_stats", "kind": "variable", "doc": "

indicates if operator calls should keep updating initial dataset statistics or not;\nif the stats_calculator was not provided with any initial dataset statistics,\nthese are always updated with every new sample.

\n", "annotation": ": bool", "default_value": "False"}, "bioimageio.core.proc_ops.UpdateStats.required_measures": {"fullname": "bioimageio.core.proc_ops.UpdateStats.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "UpdateStats.required_measures", "kind": "variable", "doc": "

\n", "annotation": ": Set[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_ops.Binarize": {"fullname": "bioimageio.core.proc_ops.Binarize", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize", "kind": "class", "doc": "

'output = tensor > threshold'.

\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.Binarize.__init__": {"fullname": "bioimageio.core.proc_ops.Binarize.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize.__init__", "kind": "function", "doc": "

\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tthreshold: Union[float, Sequence[float]],\taxis: Optional[bioimageio.spec.model.v0_5.AxisId] = None)"}, "bioimageio.core.proc_ops.Binarize.threshold": {"fullname": "bioimageio.core.proc_ops.Binarize.threshold", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize.threshold", "kind": "variable", "doc": "

\n", "annotation": ": Union[float, Sequence[float]]"}, "bioimageio.core.proc_ops.Binarize.axis": {"fullname": "bioimageio.core.proc_ops.Binarize.axis", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize.axis", "kind": "variable", "doc": "

\n", "annotation": ": Optional[bioimageio.spec.model.v0_5.AxisId]", "default_value": "None"}, "bioimageio.core.proc_ops.Binarize.get_output_shape": {"fullname": "bioimageio.core.proc_ops.Binarize.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize.get_output_shape", "kind": "function", "doc": "

\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.Binarize.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.Binarize.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize.from_proc_descr", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_5.BinarizeDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.Clip": {"fullname": "bioimageio.core.proc_ops.Clip", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip", "kind": "class", "doc": "

\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.Clip.__init__": {"fullname": "bioimageio.core.proc_ops.Clip.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip.__init__", "kind": "function", "doc": "

\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tmin: Optional[float] = None,\tmax: Optional[float] = None)"}, "bioimageio.core.proc_ops.Clip.min": {"fullname": "bioimageio.core.proc_ops.Clip.min", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip.min", "kind": "variable", "doc": "

minimum value for clipping

\n", "annotation": ": Optional[float]", "default_value": "None"}, "bioimageio.core.proc_ops.Clip.max": {"fullname": "bioimageio.core.proc_ops.Clip.max", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip.max", "kind": "variable", "doc": "

maximum value for clipping

\n", "annotation": ": Optional[float]", "default_value": "None"}, "bioimageio.core.proc_ops.Clip.get_output_shape": {"fullname": "bioimageio.core.proc_ops.Clip.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip.get_output_shape", "kind": "function", "doc": "

\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.Clip.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.Clip.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip.from_proc_descr", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_5.ClipDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.EnsureDtype": {"fullname": "bioimageio.core.proc_ops.EnsureDtype", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype", "kind": "class", "doc": "

\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.EnsureDtype.__init__": {"fullname": "bioimageio.core.proc_ops.EnsureDtype.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype.__init__", "kind": "function", "doc": "

\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tdtype: Literal['bool', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64'])"}, "bioimageio.core.proc_ops.EnsureDtype.dtype": {"fullname": "bioimageio.core.proc_ops.EnsureDtype.dtype", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype.dtype", "kind": "variable", "doc": "

\n", "annotation": ": Literal['bool', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64']"}, "bioimageio.core.proc_ops.EnsureDtype.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.EnsureDtype.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype.from_proc_descr", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tdescr: bioimageio.spec.model.v0_5.EnsureDtypeDescr,\tmember_id: bioimageio.spec.model.v0_5.TensorId):", "funcdef": "def"}, "bioimageio.core.proc_ops.EnsureDtype.get_descr": {"fullname": "bioimageio.core.proc_ops.EnsureDtype.get_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype.get_descr", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.proc_ops.EnsureDtype.get_output_shape": {"fullname": "bioimageio.core.proc_ops.EnsureDtype.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype.get_output_shape", "kind": "function", "doc": "

\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleLinear": {"fullname": "bioimageio.core.proc_ops.ScaleLinear", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear", "kind": "class", "doc": "

\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.ScaleLinear.__init__": {"fullname": "bioimageio.core.proc_ops.ScaleLinear.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear.__init__", "kind": "function", "doc": "

\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tgain: Union[float, xarray.core.dataarray.DataArray] = 1.0,\toffset: Union[float, xarray.core.dataarray.DataArray] = 0.0)"}, "bioimageio.core.proc_ops.ScaleLinear.gain": {"fullname": "bioimageio.core.proc_ops.ScaleLinear.gain", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear.gain", "kind": "variable", "doc": "

multiplicative factor

\n", "annotation": ": Union[float, xarray.core.dataarray.DataArray]", "default_value": "1.0"}, "bioimageio.core.proc_ops.ScaleLinear.offset": {"fullname": "bioimageio.core.proc_ops.ScaleLinear.offset", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear.offset", "kind": "variable", "doc": "

additive term

\n", "annotation": ": Union[float, xarray.core.dataarray.DataArray]", "default_value": "0.0"}, "bioimageio.core.proc_ops.ScaleLinear.get_output_shape": {"fullname": "bioimageio.core.proc_ops.ScaleLinear.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear.get_output_shape", "kind": "function", "doc": "

\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleLinear.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.ScaleLinear.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear.from_proc_descr", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleMeanVariance": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance", "kind": "class", "doc": "

\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.ScaleMeanVariance.__init__": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.__init__", "kind": "function", "doc": "

\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]] = None,\treference_tensor: Optional[bioimageio.spec.model.v0_5.TensorId] = None,\teps: float = 1e-06)"}, "bioimageio.core.proc_ops.ScaleMeanVariance.axes": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.axes", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.axes", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]]", "default_value": "None"}, "bioimageio.core.proc_ops.ScaleMeanVariance.reference_tensor": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.reference_tensor", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.reference_tensor", "kind": "variable", "doc": "

\n", "annotation": ": Optional[bioimageio.spec.model.v0_5.TensorId]", "default_value": "None"}, "bioimageio.core.proc_ops.ScaleMeanVariance.eps": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.eps", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.eps", "kind": "variable", "doc": "

\n", "annotation": ": float", "default_value": "1e-06"}, "bioimageio.core.proc_ops.ScaleMeanVariance.mean": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.mean", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.mean", "kind": "variable", "doc": "

\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean]"}, "bioimageio.core.proc_ops.ScaleMeanVariance.std": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.std", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.std", "kind": "variable", "doc": "

\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd]"}, "bioimageio.core.proc_ops.ScaleMeanVariance.ref_mean": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.ref_mean", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.ref_mean", "kind": "variable", "doc": "

\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean]"}, "bioimageio.core.proc_ops.ScaleMeanVariance.ref_std": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.ref_std", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.ref_std", "kind": "variable", "doc": "

\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd]"}, "bioimageio.core.proc_ops.ScaleMeanVariance.required_measures": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.required_measures", "kind": "variable", "doc": "

\n"}, "bioimageio.core.proc_ops.ScaleMeanVariance.get_output_shape": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.get_output_shape", "kind": "function", "doc": "

\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleMeanVariance.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.from_proc_descr", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr, bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleRange": {"fullname": "bioimageio.core.proc_ops.ScaleRange", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange", "kind": "class", "doc": "

\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.ScaleRange.__init__": {"fullname": "bioimageio.core.proc_ops.ScaleRange.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.__init__", "kind": "function", "doc": "

\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tlower_percentile: dataclasses.InitVar[typing.Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile, NoneType]] = None,\tupper_percentile: dataclasses.InitVar[typing.Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile, NoneType]] = None,\teps: float = 1e-06)"}, "bioimageio.core.proc_ops.ScaleRange.lower_percentile": {"fullname": "bioimageio.core.proc_ops.ScaleRange.lower_percentile", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.lower_percentile", "kind": "variable", "doc": "

\n", "annotation": ": dataclasses.InitVar[typing.Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile, NoneType]]", "default_value": "None"}, "bioimageio.core.proc_ops.ScaleRange.upper_percentile": {"fullname": "bioimageio.core.proc_ops.ScaleRange.upper_percentile", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.upper_percentile", "kind": "variable", "doc": "

\n", "annotation": ": dataclasses.InitVar[typing.Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile, NoneType]]", "default_value": "None"}, "bioimageio.core.proc_ops.ScaleRange.lower": {"fullname": "bioimageio.core.proc_ops.ScaleRange.lower", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.lower", "kind": "variable", "doc": "

\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile]"}, "bioimageio.core.proc_ops.ScaleRange.upper": {"fullname": "bioimageio.core.proc_ops.ScaleRange.upper", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.upper", "kind": "variable", "doc": "

\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile]"}, "bioimageio.core.proc_ops.ScaleRange.eps": {"fullname": "bioimageio.core.proc_ops.ScaleRange.eps", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.eps", "kind": "variable", "doc": "

\n", "annotation": ": float", "default_value": "1e-06"}, "bioimageio.core.proc_ops.ScaleRange.required_measures": {"fullname": "bioimageio.core.proc_ops.ScaleRange.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.required_measures", "kind": "variable", "doc": "

\n"}, "bioimageio.core.proc_ops.ScaleRange.get_output_shape": {"fullname": "bioimageio.core.proc_ops.ScaleRange.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.get_output_shape", "kind": "function", "doc": "

\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleRange.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.ScaleRange.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.from_proc_descr", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.ScaleRangeDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId):", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleRange.get_descr": {"fullname": "bioimageio.core.proc_ops.ScaleRange.get_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.get_descr", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.proc_ops.Sigmoid": {"fullname": "bioimageio.core.proc_ops.Sigmoid", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid", "kind": "class", "doc": "

1 / (1 + e^(-input)).

\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.Sigmoid.__init__": {"fullname": "bioimageio.core.proc_ops.Sigmoid.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid.__init__", "kind": "function", "doc": "

\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId)"}, "bioimageio.core.proc_ops.Sigmoid.required_measures": {"fullname": "bioimageio.core.proc_ops.Sigmoid.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid.required_measures", "kind": "variable", "doc": "

\n", "annotation": ": Collection[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_ops.Sigmoid.get_output_shape": {"fullname": "bioimageio.core.proc_ops.Sigmoid.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid.get_output_shape", "kind": "function", "doc": "

\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.Sigmoid.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.Sigmoid.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid.from_proc_descr", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_5.SigmoidDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.Sigmoid.get_descr": {"fullname": "bioimageio.core.proc_ops.Sigmoid.get_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid.get_descr", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance", "kind": "class", "doc": "

normalize to zero mean, unit variance.

\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.__init__": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.__init__", "kind": "function", "doc": "

\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tmean: Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean],\tstd: Union[bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd],\teps: float = 1e-06)"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.mean": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.mean", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.mean", "kind": "variable", "doc": "

\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean]"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.std": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.std", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.std", "kind": "variable", "doc": "

\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd]"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.eps": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.eps", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.eps", "kind": "variable", "doc": "

\n", "annotation": ": float", "default_value": "1e-06"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.required_measures": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.required_measures", "kind": "variable", "doc": "

\n", "annotation": ": Set[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd]]"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.get_output_shape": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.get_output_shape", "kind": "function", "doc": "

\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.from_proc_descr", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId):", "funcdef": "def"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.get_descr": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.get_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.get_descr", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance", "kind": "class", "doc": "

normalize to zero mean, unit variance with precomputed values.

\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.__init__": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.__init__", "kind": "function", "doc": "

\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tmean: Union[float, xarray.core.dataarray.DataArray],\tstd: Union[float, xarray.core.dataarray.DataArray],\teps: float = 1e-06)"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.mean": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.mean", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.mean", "kind": "variable", "doc": "

\n", "annotation": ": Union[float, xarray.core.dataarray.DataArray]"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.std": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.std", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.std", "kind": "variable", "doc": "

\n", "annotation": ": Union[float, xarray.core.dataarray.DataArray]"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.eps": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.eps", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.eps", "kind": "variable", "doc": "

\n", "annotation": ": float", "default_value": "1e-06"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.get_output_shape": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.get_output_shape", "kind": "function", "doc": "

\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.from_proc_descr", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tdescr: bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr,\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.get_descr": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.get_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.get_descr", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.proc_ops.ProcDescr": {"fullname": "bioimageio.core.proc_ops.ProcDescr", "modulename": "bioimageio.core.proc_ops", "qualname": "ProcDescr", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[typing.Annotated[typing.Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr, bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr], Discriminator(discriminator='id', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr, bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr], Discriminator(discriminator='id', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_ops.Processing": {"fullname": "bioimageio.core.proc_ops.Processing", "modulename": "bioimageio.core.proc_ops", "qualname": "Processing", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bioimageio.core.proc_ops.AddKnownDatasetStats, bioimageio.core.proc_ops.Binarize, bioimageio.core.proc_ops.Clip, bioimageio.core.proc_ops.EnsureDtype, bioimageio.core.proc_ops.FixedZeroMeanUnitVariance, bioimageio.core.proc_ops.ScaleLinear, bioimageio.core.proc_ops.ScaleMeanVariance, bioimageio.core.proc_ops.ScaleRange, bioimageio.core.proc_ops.Sigmoid, bioimageio.core.proc_ops.UpdateStats, bioimageio.core.proc_ops.ZeroMeanUnitVariance]"}, "bioimageio.core.proc_ops.get_proc_class": {"fullname": "bioimageio.core.proc_ops.get_proc_class", "modulename": "bioimageio.core.proc_ops", "qualname": "get_proc_class", "kind": "function", "doc": "

\n", "signature": "(\tproc_spec: Union[Annotated[Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr, bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr], Discriminator(discriminator='id', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr, bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr], Discriminator(discriminator='id', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]):", "funcdef": "def"}, "bioimageio.core.proc_setup": {"fullname": "bioimageio.core.proc_setup", "modulename": "bioimageio.core.proc_setup", "kind": "module", "doc": "

\n"}, "bioimageio.core.proc_setup.TensorDescr": {"fullname": "bioimageio.core.proc_setup.TensorDescr", "modulename": "bioimageio.core.proc_setup", "qualname": "TensorDescr", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_4.OutputTensorDescr, bioimageio.spec.model.v0_5.InputTensorDescr, bioimageio.spec.model.v0_5.OutputTensorDescr]"}, "bioimageio.core.proc_setup.PreAndPostprocessing": {"fullname": "bioimageio.core.proc_setup.PreAndPostprocessing", "modulename": "bioimageio.core.proc_setup", "qualname": "PreAndPostprocessing", "kind": "class", "doc": "

PreAndPostprocessing(pre, post)

\n", "bases": "typing.NamedTuple"}, "bioimageio.core.proc_setup.PreAndPostprocessing.__init__": {"fullname": "bioimageio.core.proc_setup.PreAndPostprocessing.__init__", "modulename": "bioimageio.core.proc_setup", "qualname": "PreAndPostprocessing.__init__", "kind": "function", "doc": "

Create new instance of PreAndPostprocessing(pre, post)

\n", "signature": "(\tpre: List[Union[bioimageio.core.proc_ops.AddKnownDatasetStats, bioimageio.core.proc_ops.Binarize, bioimageio.core.proc_ops.Clip, bioimageio.core.proc_ops.EnsureDtype, bioimageio.core.proc_ops.FixedZeroMeanUnitVariance, bioimageio.core.proc_ops.ScaleLinear, bioimageio.core.proc_ops.ScaleMeanVariance, bioimageio.core.proc_ops.ScaleRange, bioimageio.core.proc_ops.Sigmoid, bioimageio.core.proc_ops.UpdateStats, bioimageio.core.proc_ops.ZeroMeanUnitVariance]],\tpost: List[Union[bioimageio.core.proc_ops.AddKnownDatasetStats, bioimageio.core.proc_ops.Binarize, bioimageio.core.proc_ops.Clip, bioimageio.core.proc_ops.EnsureDtype, bioimageio.core.proc_ops.FixedZeroMeanUnitVariance, bioimageio.core.proc_ops.ScaleLinear, bioimageio.core.proc_ops.ScaleMeanVariance, bioimageio.core.proc_ops.ScaleRange, bioimageio.core.proc_ops.Sigmoid, bioimageio.core.proc_ops.UpdateStats, bioimageio.core.proc_ops.ZeroMeanUnitVariance]])"}, "bioimageio.core.proc_setup.PreAndPostprocessing.pre": {"fullname": "bioimageio.core.proc_setup.PreAndPostprocessing.pre", "modulename": "bioimageio.core.proc_setup", "qualname": "PreAndPostprocessing.pre", "kind": "variable", "doc": "

Alias for field number 0

\n", "annotation": ": List[Union[bioimageio.core.proc_ops.AddKnownDatasetStats, bioimageio.core.proc_ops.Binarize, bioimageio.core.proc_ops.Clip, bioimageio.core.proc_ops.EnsureDtype, bioimageio.core.proc_ops.FixedZeroMeanUnitVariance, bioimageio.core.proc_ops.ScaleLinear, bioimageio.core.proc_ops.ScaleMeanVariance, bioimageio.core.proc_ops.ScaleRange, bioimageio.core.proc_ops.Sigmoid, bioimageio.core.proc_ops.UpdateStats, bioimageio.core.proc_ops.ZeroMeanUnitVariance]]"}, "bioimageio.core.proc_setup.PreAndPostprocessing.post": {"fullname": "bioimageio.core.proc_setup.PreAndPostprocessing.post", "modulename": "bioimageio.core.proc_setup", "qualname": "PreAndPostprocessing.post", "kind": "variable", "doc": "

Alias for field number 1

\n", "annotation": ": List[Union[bioimageio.core.proc_ops.AddKnownDatasetStats, bioimageio.core.proc_ops.Binarize, bioimageio.core.proc_ops.Clip, bioimageio.core.proc_ops.EnsureDtype, bioimageio.core.proc_ops.FixedZeroMeanUnitVariance, bioimageio.core.proc_ops.ScaleLinear, bioimageio.core.proc_ops.ScaleMeanVariance, bioimageio.core.proc_ops.ScaleRange, bioimageio.core.proc_ops.Sigmoid, bioimageio.core.proc_ops.UpdateStats, bioimageio.core.proc_ops.ZeroMeanUnitVariance]]"}, "bioimageio.core.proc_setup.setup_pre_and_postprocessing": {"fullname": "bioimageio.core.proc_setup.setup_pre_and_postprocessing", "modulename": "bioimageio.core.proc_setup", "qualname": "setup_pre_and_postprocessing", "kind": "function", "doc": "

Get pre- and postprocessing operators for a model description.\nuserd in `bioimageio.core.create_prediction_pipeline

\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)],\tdataset_for_initial_statistics: Iterable[bioimageio.core.sample.Sample],\tkeep_updating_initial_dataset_stats: bool = False,\tfixed_dataset_stats: Optional[Mapping[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]]] = None) -> bioimageio.core.proc_setup.PreAndPostprocessing:", "funcdef": "def"}, "bioimageio.core.proc_setup.RequiredMeasures": {"fullname": "bioimageio.core.proc_setup.RequiredMeasures", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredMeasures", "kind": "class", "doc": "

RequiredMeasures(pre, post)

\n", "bases": "typing.NamedTuple"}, "bioimageio.core.proc_setup.RequiredMeasures.__init__": {"fullname": "bioimageio.core.proc_setup.RequiredMeasures.__init__", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredMeasures.__init__", "kind": "function", "doc": "

Create new instance of RequiredMeasures(pre, post)

\n", "signature": "(\tpre: Set[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]],\tpost: Set[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]])"}, "bioimageio.core.proc_setup.RequiredMeasures.pre": {"fullname": "bioimageio.core.proc_setup.RequiredMeasures.pre", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredMeasures.pre", "kind": "variable", "doc": "

Alias for field number 0

\n", "annotation": ": Set[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_setup.RequiredMeasures.post": {"fullname": "bioimageio.core.proc_setup.RequiredMeasures.post", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredMeasures.post", "kind": "variable", "doc": "

Alias for field number 1

\n", "annotation": ": Set[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_setup.RequiredDatasetMeasures": {"fullname": "bioimageio.core.proc_setup.RequiredDatasetMeasures", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredDatasetMeasures", "kind": "class", "doc": "

RequiredDatasetMeasures(pre, post)

\n", "bases": "typing.NamedTuple"}, "bioimageio.core.proc_setup.RequiredDatasetMeasures.__init__": {"fullname": "bioimageio.core.proc_setup.RequiredDatasetMeasures.__init__", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredDatasetMeasures.__init__", "kind": "function", "doc": "

Create new instance of RequiredDatasetMeasures(pre, post)

\n", "signature": "(\tpre: Set[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]],\tpost: Set[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]])"}, "bioimageio.core.proc_setup.RequiredDatasetMeasures.pre": {"fullname": "bioimageio.core.proc_setup.RequiredDatasetMeasures.pre", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredDatasetMeasures.pre", "kind": "variable", "doc": "

Alias for field number 0

\n", "annotation": ": Set[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_setup.RequiredDatasetMeasures.post": {"fullname": "bioimageio.core.proc_setup.RequiredDatasetMeasures.post", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredDatasetMeasures.post", "kind": "variable", "doc": "

Alias for field number 1

\n", "annotation": ": Set[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_setup.RequiredSampleMeasures": {"fullname": "bioimageio.core.proc_setup.RequiredSampleMeasures", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredSampleMeasures", "kind": "class", "doc": "

RequiredSampleMeasures(pre, post)

\n", "bases": "typing.NamedTuple"}, "bioimageio.core.proc_setup.RequiredSampleMeasures.__init__": {"fullname": "bioimageio.core.proc_setup.RequiredSampleMeasures.__init__", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredSampleMeasures.__init__", "kind": "function", "doc": "

Create new instance of RequiredSampleMeasures(pre, post)

\n", "signature": "(\tpre: Set[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]],\tpost: Set[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]])"}, "bioimageio.core.proc_setup.RequiredSampleMeasures.pre": {"fullname": "bioimageio.core.proc_setup.RequiredSampleMeasures.pre", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredSampleMeasures.pre", "kind": "variable", "doc": "

Alias for field number 0

\n", "annotation": ": Set[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_setup.RequiredSampleMeasures.post": {"fullname": "bioimageio.core.proc_setup.RequiredSampleMeasures.post", "modulename": "bioimageio.core.proc_setup", "qualname": "RequiredSampleMeasures.post", "kind": "variable", "doc": "

Alias for field number 1

\n", "annotation": ": Set[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_setup.get_requried_measures": {"fullname": "bioimageio.core.proc_setup.get_requried_measures", "modulename": "bioimageio.core.proc_setup", "qualname": "get_requried_measures", "kind": "function", "doc": "

\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]) -> bioimageio.core.proc_setup.RequiredMeasures:", "funcdef": "def"}, "bioimageio.core.proc_setup.get_required_dataset_measures": {"fullname": "bioimageio.core.proc_setup.get_required_dataset_measures", "modulename": "bioimageio.core.proc_setup", "qualname": "get_required_dataset_measures", "kind": "function", "doc": "

\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]) -> bioimageio.core.proc_setup.RequiredDatasetMeasures:", "funcdef": "def"}, "bioimageio.core.proc_setup.get_requried_sample_measures": {"fullname": "bioimageio.core.proc_setup.get_requried_sample_measures", "modulename": "bioimageio.core.proc_setup", "qualname": "get_requried_sample_measures", "kind": "function", "doc": "

\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]) -> bioimageio.core.proc_setup.RequiredSampleMeasures:", "funcdef": "def"}, "bioimageio.core.sample": {"fullname": "bioimageio.core.sample", "modulename": "bioimageio.core.sample", "kind": "module", "doc": "

\n"}, "bioimageio.core.sample.Sample": {"fullname": "bioimageio.core.sample.Sample", "modulename": "bioimageio.core.sample", "qualname": "Sample", "kind": "class", "doc": "

A dataset sample

\n"}, "bioimageio.core.sample.Sample.__init__": {"fullname": "bioimageio.core.sample.Sample.__init__", "modulename": "bioimageio.core.sample", "qualname": "Sample.__init__", "kind": "function", "doc": "

\n", "signature": "(\tmembers: Dict[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.tensor.Tensor],\tstat: Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]],\tid: Hashable)"}, "bioimageio.core.sample.Sample.members": {"fullname": "bioimageio.core.sample.Sample.members", "modulename": "bioimageio.core.sample", "qualname": "Sample.members", "kind": "variable", "doc": "

the sample's tensors

\n", "annotation": ": Dict[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.tensor.Tensor]"}, "bioimageio.core.sample.Sample.stat": {"fullname": "bioimageio.core.sample.Sample.stat", "modulename": "bioimageio.core.sample", "qualname": "Sample.stat", "kind": "variable", "doc": "

sample and dataset statistics

\n", "annotation": ": Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]"}, "bioimageio.core.sample.Sample.id": {"fullname": "bioimageio.core.sample.Sample.id", "modulename": "bioimageio.core.sample", "qualname": "Sample.id", "kind": "variable", "doc": "

identifier within the sample's dataset

\n", "annotation": ": Hashable"}, "bioimageio.core.sample.Sample.shape": {"fullname": "bioimageio.core.sample.Sample.shape", "modulename": "bioimageio.core.sample", "qualname": "Sample.shape", "kind": "variable", "doc": "

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]"}, "bioimageio.core.sample.Sample.split_into_blocks": {"fullname": "bioimageio.core.sample.Sample.split_into_blocks", "modulename": "bioimageio.core.sample", "qualname": "Sample.split_into_blocks", "kind": "function", "doc": "

\n", "signature": "(\tself,\tblock_shapes: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\thalo: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, Union[int, Tuple[int, int], bioimageio.core.common.Halo]]],\tpad_mode: Literal['edge', 'reflect', 'symmetric'],\tbroadcast: bool = False) -> Tuple[int, Iterable[bioimageio.core.sample.SampleBlockWithOrigin]]:", "funcdef": "def"}, "bioimageio.core.sample.Sample.as_single_block": {"fullname": "bioimageio.core.sample.Sample.as_single_block", "modulename": "bioimageio.core.sample", "qualname": "Sample.as_single_block", "kind": "function", "doc": "

\n", "signature": "(\tself,\thalo: Optional[Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.Halo]]] = None):", "funcdef": "def"}, "bioimageio.core.sample.Sample.from_blocks": {"fullname": "bioimageio.core.sample.Sample.from_blocks", "modulename": "bioimageio.core.sample", "qualname": "Sample.from_blocks", "kind": "function", "doc": "

\n", "signature": "(\tcls,\tsample_blocks: Iterable[bioimageio.core.sample.SampleBlock],\t*,\tfill_value: float = nan) -> Self:", "funcdef": "def"}, "bioimageio.core.sample.SampleBlockBase": {"fullname": "bioimageio.core.sample.SampleBlockBase", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase", "kind": "class", "doc": "

base class for SampleBlockMeta and SampleBlock

\n", "bases": "typing.Generic[~BlockT]"}, "bioimageio.core.sample.SampleBlockBase.__init__": {"fullname": "bioimageio.core.sample.SampleBlockBase.__init__", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.__init__", "kind": "function", "doc": "

\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tsample_id: Hashable,\tblocks: Dict[bioimageio.spec.model.v0_5.TensorId, ~BlockT],\tblock_index: int,\tblocks_in_sample: int)"}, "bioimageio.core.sample.SampleBlockBase.sample_shape": {"fullname": "bioimageio.core.sample.SampleBlockBase.sample_shape", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.sample_shape", "kind": "variable", "doc": "

the sample shape this block represents a part of

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]"}, "bioimageio.core.sample.SampleBlockBase.sample_id": {"fullname": "bioimageio.core.sample.SampleBlockBase.sample_id", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.sample_id", "kind": "variable", "doc": "

identifier for the sample within its dataset

\n", "annotation": ": Hashable"}, "bioimageio.core.sample.SampleBlockBase.blocks": {"fullname": "bioimageio.core.sample.SampleBlockBase.blocks", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.blocks", "kind": "variable", "doc": "

Individual tensor blocks comprising this sample block

\n", "annotation": ": Dict[bioimageio.spec.model.v0_5.TensorId, ~BlockT]"}, "bioimageio.core.sample.SampleBlockBase.block_index": {"fullname": "bioimageio.core.sample.SampleBlockBase.block_index", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.block_index", "kind": "variable", "doc": "

the n-th block of the sample

\n", "annotation": ": int"}, "bioimageio.core.sample.SampleBlockBase.blocks_in_sample": {"fullname": "bioimageio.core.sample.SampleBlockBase.blocks_in_sample", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.blocks_in_sample", "kind": "variable", "doc": "

total number of blocks in the sample

\n", "annotation": ": int"}, "bioimageio.core.sample.SampleBlockBase.shape": {"fullname": "bioimageio.core.sample.SampleBlockBase.shape", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.shape", "kind": "variable", "doc": "

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]"}, "bioimageio.core.sample.SampleBlockBase.inner_shape": {"fullname": "bioimageio.core.sample.SampleBlockBase.inner_shape", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.inner_shape", "kind": "variable", "doc": "

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]"}, "bioimageio.core.sample.LinearSampleAxisTransform": {"fullname": "bioimageio.core.sample.LinearSampleAxisTransform", "modulename": "bioimageio.core.sample", "qualname": "LinearSampleAxisTransform", "kind": "class", "doc": "

\n", "bases": "bioimageio.core.block_meta.LinearAxisTransform"}, "bioimageio.core.sample.LinearSampleAxisTransform.__init__": {"fullname": "bioimageio.core.sample.LinearSampleAxisTransform.__init__", "modulename": "bioimageio.core.sample", "qualname": "LinearSampleAxisTransform.__init__", "kind": "function", "doc": "

\n", "signature": "(\taxis: bioimageio.spec.model.v0_5.AxisId,\tscale: float,\toffset: int,\tmember: bioimageio.spec.model.v0_5.TensorId)"}, "bioimageio.core.sample.LinearSampleAxisTransform.member": {"fullname": "bioimageio.core.sample.LinearSampleAxisTransform.member", "modulename": "bioimageio.core.sample", "qualname": "LinearSampleAxisTransform.member", "kind": "variable", "doc": "

\n", "annotation": ": bioimageio.spec.model.v0_5.TensorId"}, "bioimageio.core.sample.SampleBlockMeta": {"fullname": "bioimageio.core.sample.SampleBlockMeta", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockMeta", "kind": "class", "doc": "

Meta data of a dataset sample block

\n", "bases": "bioimageio.core.sample.SampleBlockBase[bioimageio.core.block_meta.BlockMeta]"}, "bioimageio.core.sample.SampleBlockMeta.__init__": {"fullname": "bioimageio.core.sample.SampleBlockMeta.__init__", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockMeta.__init__", "kind": "function", "doc": "

\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tsample_id: Hashable,\tblocks: Dict[bioimageio.spec.model.v0_5.TensorId, ~BlockT],\tblock_index: int,\tblocks_in_sample: int)"}, "bioimageio.core.sample.SampleBlockMeta.get_transformed": {"fullname": "bioimageio.core.sample.SampleBlockMeta.get_transformed", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockMeta.get_transformed", "kind": "function", "doc": "

\n", "signature": "(\tself,\tnew_axes: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, Union[bioimageio.core.sample.LinearSampleAxisTransform, int]]]) -> Self:", "funcdef": "def"}, "bioimageio.core.sample.SampleBlockMeta.with_data": {"fullname": "bioimageio.core.sample.SampleBlockMeta.with_data", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockMeta.with_data", "kind": "function", "doc": "

\n", "signature": "(\tself,\tdata: Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.tensor.Tensor],\t*,\tstat: Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]]) -> bioimageio.core.sample.SampleBlock:", "funcdef": "def"}, "bioimageio.core.sample.SampleBlock": {"fullname": "bioimageio.core.sample.SampleBlock", "modulename": "bioimageio.core.sample", "qualname": "SampleBlock", "kind": "class", "doc": "

A block of a dataset sample

\n", "bases": "bioimageio.core.sample.SampleBlockBase[bioimageio.core.block.Block]"}, "bioimageio.core.sample.SampleBlock.__init__": {"fullname": "bioimageio.core.sample.SampleBlock.__init__", "modulename": "bioimageio.core.sample", "qualname": "SampleBlock.__init__", "kind": "function", "doc": "

\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tsample_id: Hashable,\tblocks: Dict[bioimageio.spec.model.v0_5.TensorId, ~BlockT],\tblock_index: int,\tblocks_in_sample: int,\tstat: Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]])"}, "bioimageio.core.sample.SampleBlock.stat": {"fullname": "bioimageio.core.sample.SampleBlock.stat", "modulename": "bioimageio.core.sample", "qualname": "SampleBlock.stat", "kind": "variable", "doc": "

computed statistics

\n", "annotation": ": Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]"}, "bioimageio.core.sample.SampleBlock.members": {"fullname": "bioimageio.core.sample.SampleBlock.members", "modulename": "bioimageio.core.sample", "qualname": "SampleBlock.members", "kind": "variable", "doc": "

the sample block's tensors

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.tensor.Tensor]"}, "bioimageio.core.sample.SampleBlock.get_transformed_meta": {"fullname": "bioimageio.core.sample.SampleBlock.get_transformed_meta", "modulename": "bioimageio.core.sample", "qualname": "SampleBlock.get_transformed_meta", "kind": "function", "doc": "

\n", "signature": "(\tself,\tnew_axes: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, Union[bioimageio.core.sample.LinearSampleAxisTransform, int]]]) -> bioimageio.core.sample.SampleBlockMeta:", "funcdef": "def"}, "bioimageio.core.sample.SampleBlockWithOrigin": {"fullname": "bioimageio.core.sample.SampleBlockWithOrigin", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockWithOrigin", "kind": "class", "doc": "

\n", "bases": "bioimageio.core.sample.SampleBlockBase[bioimageio.core.block.Block]"}, "bioimageio.core.sample.SampleBlockWithOrigin.__init__": {"fullname": "bioimageio.core.sample.SampleBlockWithOrigin.__init__", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockWithOrigin.__init__", "kind": "function", "doc": "

\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tsample_id: Hashable,\tblocks: Dict[bioimageio.spec.model.v0_5.TensorId, ~BlockT],\tblock_index: int,\tblocks_in_sample: int,\tstat: Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]],\torigin: bioimageio.core.sample.Sample)"}, "bioimageio.core.sample.SampleBlockWithOrigin.origin": {"fullname": "bioimageio.core.sample.SampleBlockWithOrigin.origin", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockWithOrigin.origin", "kind": "variable", "doc": "

the sample this sample black was taken from

\n", "annotation": ": bioimageio.core.sample.Sample"}, "bioimageio.core.sample.sample_block_meta_generator": {"fullname": "bioimageio.core.sample.sample_block_meta_generator", "modulename": "bioimageio.core.sample", "qualname": "sample_block_meta_generator", "kind": "function", "doc": "

\n", "signature": "(\tblocks: Iterable[Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.block_meta.BlockMeta]],\t*,\tsample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tsample_id: Hashable):", "funcdef": "def"}, "bioimageio.core.sample.sample_block_generator": {"fullname": "bioimageio.core.sample.sample_block_generator", "modulename": "bioimageio.core.sample", "qualname": "sample_block_generator", "kind": "function", "doc": "

\n", "signature": "(\tblocks: Iterable[Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.block_meta.BlockMeta]],\t*,\torigin: bioimageio.core.sample.Sample,\tpad_mode: Literal['edge', 'reflect', 'symmetric']):", "funcdef": "def"}, "bioimageio.core.stat_calculators": {"fullname": "bioimageio.core.stat_calculators", "modulename": "bioimageio.core.stat_calculators", "kind": "module", "doc": "

\n"}, "bioimageio.core.stat_calculators.MeanCalculator": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator", "kind": "class", "doc": "

to calculate sample and dataset mean for in-memory samples

\n"}, "bioimageio.core.stat_calculators.MeanCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]])"}, "bioimageio.core.stat_calculators.MeanCalculator.compute": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator.compute", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator.compute", "kind": "function", "doc": "

\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[bioimageio.core.stat_measures.SampleMean, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanCalculator.update": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator.update", "kind": "function", "doc": "

\n", "signature": "(self, sample: bioimageio.core.sample.Sample) -> None:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanCalculator.compute_and_update": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator.compute_and_update", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator.compute_and_update", "kind": "function", "doc": "

\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[bioimageio.core.stat_measures.SampleMean, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanCalculator.finalize": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator.finalize", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator.finalize", "kind": "function", "doc": "

\n", "signature": "(\tself) -> Dict[bioimageio.core.stat_measures.DatasetMean, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanVarStdCalculator": {"fullname": "bioimageio.core.stat_calculators.MeanVarStdCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanVarStdCalculator", "kind": "class", "doc": "

to calculate sample and dataset mean, variance or standard deviation

\n"}, "bioimageio.core.stat_calculators.MeanVarStdCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.MeanVarStdCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanVarStdCalculator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]])"}, "bioimageio.core.stat_calculators.MeanVarStdCalculator.compute": {"fullname": "bioimageio.core.stat_calculators.MeanVarStdCalculator.compute", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanVarStdCalculator.compute", "kind": "function", "doc": "

\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleStd], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanVarStdCalculator.update": {"fullname": "bioimageio.core.stat_calculators.MeanVarStdCalculator.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanVarStdCalculator.update", "kind": "function", "doc": "

\n", "signature": "(self, sample: bioimageio.core.sample.Sample):", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanVarStdCalculator.finalize": {"fullname": "bioimageio.core.stat_calculators.MeanVarStdCalculator.finalize", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanVarStdCalculator.finalize", "kind": "function", "doc": "

\n", "signature": "(\tself) -> Dict[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetStd], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.SamplePercentilesCalculator": {"fullname": "bioimageio.core.stat_calculators.SamplePercentilesCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "SamplePercentilesCalculator", "kind": "class", "doc": "

to calculate sample percentiles

\n"}, "bioimageio.core.stat_calculators.SamplePercentilesCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.SamplePercentilesCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "SamplePercentilesCalculator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]],\tqs: Collection[float])"}, "bioimageio.core.stat_calculators.SamplePercentilesCalculator.compute": {"fullname": "bioimageio.core.stat_calculators.SamplePercentilesCalculator.compute", "modulename": "bioimageio.core.stat_calculators", "qualname": "SamplePercentilesCalculator.compute", "kind": "function", "doc": "

\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[bioimageio.core.stat_measures.SampleQuantile, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanPercentilesCalculator": {"fullname": "bioimageio.core.stat_calculators.MeanPercentilesCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanPercentilesCalculator", "kind": "class", "doc": "

to calculate dataset percentiles heuristically by averaging across samples\nnote: the returned dataset percentiles are an estiamte and not mathematically correct

\n"}, "bioimageio.core.stat_calculators.MeanPercentilesCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.MeanPercentilesCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanPercentilesCalculator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]],\tqs: Collection[float])"}, "bioimageio.core.stat_calculators.MeanPercentilesCalculator.update": {"fullname": "bioimageio.core.stat_calculators.MeanPercentilesCalculator.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanPercentilesCalculator.update", "kind": "function", "doc": "

\n", "signature": "(self, sample: bioimageio.core.sample.Sample):", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanPercentilesCalculator.finalize": {"fullname": "bioimageio.core.stat_calculators.MeanPercentilesCalculator.finalize", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanPercentilesCalculator.finalize", "kind": "function", "doc": "

\n", "signature": "(\tself) -> Dict[bioimageio.core.stat_measures.DatasetPercentile, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.CrickPercentilesCalculator": {"fullname": "bioimageio.core.stat_calculators.CrickPercentilesCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "CrickPercentilesCalculator", "kind": "class", "doc": "

to calculate dataset percentiles with the experimental crick libray

\n"}, "bioimageio.core.stat_calculators.CrickPercentilesCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.CrickPercentilesCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "CrickPercentilesCalculator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]],\tqs: Collection[float])"}, "bioimageio.core.stat_calculators.CrickPercentilesCalculator.update": {"fullname": "bioimageio.core.stat_calculators.CrickPercentilesCalculator.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "CrickPercentilesCalculator.update", "kind": "function", "doc": "

\n", "signature": "(self, part: bioimageio.core.sample.Sample):", "funcdef": "def"}, "bioimageio.core.stat_calculators.CrickPercentilesCalculator.finalize": {"fullname": "bioimageio.core.stat_calculators.CrickPercentilesCalculator.finalize", "modulename": "bioimageio.core.stat_calculators", "qualname": "CrickPercentilesCalculator.finalize", "kind": "function", "doc": "

\n", "signature": "(\tself) -> Dict[bioimageio.core.stat_measures.DatasetPercentile, Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator": {"fullname": "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "NaiveSampleMeasureCalculator", "kind": "class", "doc": "

wrapper for measures to match interface of other sample measure calculators

\n"}, "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "NaiveSampleMeasureCalculator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\tmeasure: Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)])"}, "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.tensor_name": {"fullname": "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.tensor_name", "modulename": "bioimageio.core.stat_calculators", "qualname": "NaiveSampleMeasureCalculator.tensor_name", "kind": "variable", "doc": "

\n"}, "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.measure": {"fullname": "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.measure", "modulename": "bioimageio.core.stat_calculators", "qualname": "NaiveSampleMeasureCalculator.measure", "kind": "variable", "doc": "

\n"}, "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.compute": {"fullname": "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.compute", "modulename": "bioimageio.core.stat_calculators", "qualname": "NaiveSampleMeasureCalculator.compute", "kind": "function", "doc": "

\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.SampleMeasureCalculator": {"fullname": "bioimageio.core.stat_calculators.SampleMeasureCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "SampleMeasureCalculator", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bioimageio.core.stat_calculators.MeanCalculator, bioimageio.core.stat_calculators.MeanVarStdCalculator, bioimageio.core.stat_calculators.SamplePercentilesCalculator, bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator]"}, "bioimageio.core.stat_calculators.DatasetMeasureCalculator": {"fullname": "bioimageio.core.stat_calculators.DatasetMeasureCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "DatasetMeasureCalculator", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bioimageio.core.stat_calculators.MeanCalculator, bioimageio.core.stat_calculators.MeanVarStdCalculator, bioimageio.core.stat_calculators.MeanPercentilesCalculator]"}, "bioimageio.core.stat_calculators.StatsCalculator": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator", "kind": "class", "doc": "

Estimates dataset statistics and computes sample statistics efficiently

\n"}, "bioimageio.core.stat_calculators.StatsCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tmeasures: Collection[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]],\tinitial_dataset_measures: Optional[Mapping[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]]] = None)"}, "bioimageio.core.stat_calculators.StatsCalculator.sample_count": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.sample_count", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.sample_count", "kind": "variable", "doc": "

\n"}, "bioimageio.core.stat_calculators.StatsCalculator.has_dataset_measures": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.has_dataset_measures", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.has_dataset_measures", "kind": "variable", "doc": "

\n"}, "bioimageio.core.stat_calculators.StatsCalculator.update": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.update", "kind": "function", "doc": "

\n", "signature": "(\tself,\tsample: Union[bioimageio.core.sample.Sample, Iterable[bioimageio.core.sample.Sample]]) -> None:", "funcdef": "def"}, "bioimageio.core.stat_calculators.StatsCalculator.finalize": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.finalize", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.finalize", "kind": "function", "doc": "

returns aggregated dataset statistics

\n", "signature": "(\tself) -> Dict[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.StatsCalculator.update_and_get_all": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.update_and_get_all", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.update_and_get_all", "kind": "function", "doc": "

Returns sample as well as updated dataset statistics

\n", "signature": "(\tself,\tsample: Union[bioimageio.core.sample.Sample, Iterable[bioimageio.core.sample.Sample]]) -> Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.StatsCalculator.skip_update_and_get_all": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.skip_update_and_get_all", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.skip_update_and_get_all", "kind": "function", "doc": "

Returns sample as well as previously computed dataset statistics

\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.get_measure_calculators": {"fullname": "bioimageio.core.stat_calculators.get_measure_calculators", "modulename": "bioimageio.core.stat_calculators", "qualname": "get_measure_calculators", "kind": "function", "doc": "

determines which calculators are needed to compute the required measures efficiently

\n", "signature": "(\trequired_measures: Iterable[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]) -> Tuple[List[Union[bioimageio.core.stat_calculators.MeanCalculator, bioimageio.core.stat_calculators.MeanVarStdCalculator, bioimageio.core.stat_calculators.SamplePercentilesCalculator, bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator]], List[Union[bioimageio.core.stat_calculators.MeanCalculator, bioimageio.core.stat_calculators.MeanVarStdCalculator, bioimageio.core.stat_calculators.MeanPercentilesCalculator]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.compute_dataset_measures": {"fullname": "bioimageio.core.stat_calculators.compute_dataset_measures", "modulename": "bioimageio.core.stat_calculators", "qualname": "compute_dataset_measures", "kind": "function", "doc": "

compute all dataset measures for the given dataset

\n", "signature": "(\tmeasures: Iterable[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]],\tdataset: Iterable[bioimageio.core.sample.Sample]) -> Dict[Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.compute_sample_measures": {"fullname": "bioimageio.core.stat_calculators.compute_sample_measures", "modulename": "bioimageio.core.stat_calculators", "qualname": "compute_sample_measures", "kind": "function", "doc": "

compute all sample measures for the given sample

\n", "signature": "(\tmeasures: Iterable[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]],\tsample: bioimageio.core.sample.Sample) -> Dict[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.compute_measures": {"fullname": "bioimageio.core.stat_calculators.compute_measures", "modulename": "bioimageio.core.stat_calculators", "qualname": "compute_measures", "kind": "function", "doc": "

compute all measures for the given dataset\nsample measures are computed for the last sample in dataset

\n", "signature": "(\tmeasures: Iterable[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]],\tdataset: Iterable[bioimageio.core.sample.Sample]) -> Dict[Annotated[Union[Annotated[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.TDigest": {"fullname": "bioimageio.core.stat_calculators.TDigest", "modulename": "bioimageio.core.stat_calculators", "qualname": "TDigest", "kind": "class", "doc": "

\n"}, "bioimageio.core.stat_calculators.TDigest.update": {"fullname": "bioimageio.core.stat_calculators.TDigest.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "TDigest.update", "kind": "function", "doc": "

\n", "signature": "(self, obj: Any):", "funcdef": "def"}, "bioimageio.core.stat_calculators.TDigest.quantile": {"fullname": "bioimageio.core.stat_calculators.TDigest.quantile", "modulename": "bioimageio.core.stat_calculators", "qualname": "TDigest.quantile", "kind": "function", "doc": "

\n", "signature": "(self, q: Any) -> Any:", "funcdef": "def"}, "bioimageio.core.stat_calculators.DatasetPercentilesCalculator": {"fullname": "bioimageio.core.stat_calculators.DatasetPercentilesCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "DatasetPercentilesCalculator", "kind": "variable", "doc": "

\n", "annotation": ": Type[Union[bioimageio.core.stat_calculators.MeanPercentilesCalculator, bioimageio.core.stat_calculators.CrickPercentilesCalculator]]", "default_value": "<class 'bioimageio.core.stat_calculators.MeanPercentilesCalculator'>"}, "bioimageio.core.stat_measures": {"fullname": "bioimageio.core.stat_measures", "modulename": "bioimageio.core.stat_measures", "kind": "module", "doc": "

\n"}, "bioimageio.core.stat_measures.tensor_custom_before_validator": {"fullname": "bioimageio.core.stat_measures.tensor_custom_before_validator", "modulename": "bioimageio.core.stat_measures", "qualname": "tensor_custom_before_validator", "kind": "function", "doc": "

\n", "signature": "(data: Union[bioimageio.core.tensor.Tensor, Mapping[str, Any]]):", "funcdef": "def"}, "bioimageio.core.stat_measures.tensor_custom_serializer": {"fullname": "bioimageio.core.stat_measures.tensor_custom_serializer", "modulename": "bioimageio.core.stat_measures", "qualname": "tensor_custom_serializer", "kind": "function", "doc": "

\n", "signature": "(t: bioimageio.core.tensor.Tensor) -> Dict[str, Any]:", "funcdef": "def"}, "bioimageio.core.stat_measures.MeasureValue": {"fullname": "bioimageio.core.stat_measures.MeasureValue", "modulename": "bioimageio.core.stat_measures", "qualname": "MeasureValue", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[float, typing.Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]"}, "bioimageio.core.stat_measures.SampleLike": {"fullname": "bioimageio.core.stat_measures.SampleLike", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleLike", "kind": "class", "doc": "

Base class for protocol classes.

\n\n

Protocol classes are defined as::

\n\n
class Proto(Protocol):\n    def meth(self) -> int:\n        ...\n
\n\n

Such classes are primarily used with static type checkers that recognize\nstructural subtyping (static duck-typing).

\n\n

For example::

\n\n
class C:\n    def meth(self) -> int:\n        return 0\n\ndef func(x: Proto) -> int:\n    return x.meth()\n\nfunc(C())  # Passes static type check\n
\n\n

See PEP 544 for details. Protocol classes decorated with\n@typing.runtime_checkable act as simple-minded runtime protocols that check\nonly the presence of given attributes, ignoring their type signatures.\nProtocol classes can be generic, they are defined as::

\n\n
class GenProto[T](Protocol):\n    def meth(self) -> T:\n        ...\n
\n", "bases": "typing.Protocol"}, "bioimageio.core.stat_measures.SampleLike.__init__": {"fullname": "bioimageio.core.stat_measures.SampleLike.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleLike.__init__", "kind": "function", "doc": "

\n", "signature": "(*args, **kwargs)"}, "bioimageio.core.stat_measures.SampleLike.members": {"fullname": "bioimageio.core.stat_measures.SampleLike.members", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleLike.members", "kind": "variable", "doc": "

\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.tensor.Tensor]"}, "bioimageio.core.stat_measures.MeasureBase": {"fullname": "bioimageio.core.stat_measures.MeasureBase", "modulename": "bioimageio.core.stat_measures", "qualname": "MeasureBase", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.9/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of the class variables defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The synthesized __init__ [Signature][inspect.Signature] of the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The core schema of the model.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a [`RootModel`][pydantic.root_model.RootModel].\n__pydantic_serializer__: The `pydantic-core` `SchemaSerializer` used to dump instances of the model.\n__pydantic_validator__: The `pydantic-core` `SchemaValidator` used to validate instances of the model.\n\n__pydantic_extra__: A dictionary containing extra values, if [`extra`][pydantic.config.ConfigDict.extra]\n    is set to `'allow'`.\n__pydantic_fields_set__: The names of fields explicitly set during instantiation.\n__pydantic_private__: Values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "bioimageio.core.stat_measures.MeasureBase.member_id": {"fullname": "bioimageio.core.stat_measures.MeasureBase.member_id", "modulename": "bioimageio.core.stat_measures", "qualname": "MeasureBase.member_id", "kind": "variable", "doc": "

\n", "annotation": ": bioimageio.spec.model.v0_5.TensorId"}, "bioimageio.core.stat_measures.MeasureBase.model_config": {"fullname": "bioimageio.core.stat_measures.MeasureBase.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "MeasureBase.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.MeasureBase.model_fields": {"fullname": "bioimageio.core.stat_measures.MeasureBase.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "MeasureBase.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True)}"}, "bioimageio.core.stat_measures.MeasureBase.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.MeasureBase.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "MeasureBase.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.SampleMeasureBase": {"fullname": "bioimageio.core.stat_measures.SampleMeasureBase", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMeasureBase", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.9/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of the class variables defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The synthesized __init__ [Signature][inspect.Signature] of the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The core schema of the model.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a [`RootModel`][pydantic.root_model.RootModel].\n__pydantic_serializer__: The `pydantic-core` `SchemaSerializer` used to dump instances of the model.\n__pydantic_validator__: The `pydantic-core` `SchemaValidator` used to validate instances of the model.\n\n__pydantic_extra__: A dictionary containing extra values, if [`extra`][pydantic.config.ConfigDict.extra]\n    is set to `'allow'`.\n__pydantic_fields_set__: The names of fields explicitly set during instantiation.\n__pydantic_private__: Values of private attributes set on the model instance.\n
\n", "bases": "MeasureBase, abc.ABC"}, "bioimageio.core.stat_measures.SampleMeasureBase.scope": {"fullname": "bioimageio.core.stat_measures.SampleMeasureBase.scope", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMeasureBase.scope", "kind": "variable", "doc": "

\n", "annotation": ": Literal['sample']"}, "bioimageio.core.stat_measures.SampleMeasureBase.compute": {"fullname": "bioimageio.core.stat_measures.SampleMeasureBase.compute", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMeasureBase.compute", "kind": "function", "doc": "

compute the measure

\n", "signature": "(\tself,\tsample: bioimageio.core.stat_measures.SampleLike) -> Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]:", "funcdef": "def"}, "bioimageio.core.stat_measures.SampleMeasureBase.model_config": {"fullname": "bioimageio.core.stat_measures.SampleMeasureBase.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMeasureBase.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.SampleMeasureBase.model_fields": {"fullname": "bioimageio.core.stat_measures.SampleMeasureBase.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMeasureBase.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True), 'scope': FieldInfo(annotation=Literal['sample'], required=False, default='sample')}"}, "bioimageio.core.stat_measures.SampleMeasureBase.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.SampleMeasureBase.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMeasureBase.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.DatasetMeasureBase": {"fullname": "bioimageio.core.stat_measures.DatasetMeasureBase", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMeasureBase", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.9/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of the class variables defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The synthesized __init__ [Signature][inspect.Signature] of the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The core schema of the model.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a [`RootModel`][pydantic.root_model.RootModel].\n__pydantic_serializer__: The `pydantic-core` `SchemaSerializer` used to dump instances of the model.\n__pydantic_validator__: The `pydantic-core` `SchemaValidator` used to validate instances of the model.\n\n__pydantic_extra__: A dictionary containing extra values, if [`extra`][pydantic.config.ConfigDict.extra]\n    is set to `'allow'`.\n__pydantic_fields_set__: The names of fields explicitly set during instantiation.\n__pydantic_private__: Values of private attributes set on the model instance.\n
\n", "bases": "MeasureBase, abc.ABC"}, "bioimageio.core.stat_measures.DatasetMeasureBase.scope": {"fullname": "bioimageio.core.stat_measures.DatasetMeasureBase.scope", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMeasureBase.scope", "kind": "variable", "doc": "

\n", "annotation": ": Literal['dataset']"}, "bioimageio.core.stat_measures.DatasetMeasureBase.model_config": {"fullname": "bioimageio.core.stat_measures.DatasetMeasureBase.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMeasureBase.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.DatasetMeasureBase.model_fields": {"fullname": "bioimageio.core.stat_measures.DatasetMeasureBase.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMeasureBase.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True), 'scope': FieldInfo(annotation=Literal['dataset'], required=False, default='dataset')}"}, "bioimageio.core.stat_measures.DatasetMeasureBase.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.DatasetMeasureBase.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMeasureBase.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.SampleMean": {"fullname": "bioimageio.core.stat_measures.SampleMean", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMean", "kind": "class", "doc": "

The mean value of a single tensor

\n", "bases": "_Mean, SampleMeasureBase"}, "bioimageio.core.stat_measures.SampleMean.compute": {"fullname": "bioimageio.core.stat_measures.SampleMean.compute", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMean.compute", "kind": "function", "doc": "

compute the measure

\n", "signature": "(\tself,\tsample: bioimageio.core.stat_measures.SampleLike) -> Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]:", "funcdef": "def"}, "bioimageio.core.stat_measures.SampleMean.model_post_init": {"fullname": "bioimageio.core.stat_measures.SampleMean.model_post_init", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMean.model_post_init", "kind": "function", "doc": "

Override this method to perform additional initialization after __init__ and model_construct.\nThis is useful if you want to do some validation that requires the entire model to be initialized.

\n", "signature": "(self, _SampleMean__context: Any):", "funcdef": "def"}, "bioimageio.core.stat_measures.SampleMean.model_config": {"fullname": "bioimageio.core.stat_measures.SampleMean.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMean.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.SampleMean.model_fields": {"fullname": "bioimageio.core.stat_measures.SampleMean.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMean.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True), 'scope': FieldInfo(annotation=Literal['sample'], required=False, default='sample'), 'name': FieldInfo(annotation=Literal['mean'], required=False, default='mean'), 'axes': FieldInfo(annotation=Union[Tuple[AxisId, ...], NoneType], required=False, default=None)}"}, "bioimageio.core.stat_measures.SampleMean.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.SampleMean.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMean.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.DatasetMean": {"fullname": "bioimageio.core.stat_measures.DatasetMean", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMean", "kind": "class", "doc": "

The mean value across multiple samples

\n", "bases": "_Mean, DatasetMeasureBase"}, "bioimageio.core.stat_measures.DatasetMean.model_post_init": {"fullname": "bioimageio.core.stat_measures.DatasetMean.model_post_init", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMean.model_post_init", "kind": "function", "doc": "

Override this method to perform additional initialization after __init__ and model_construct.\nThis is useful if you want to do some validation that requires the entire model to be initialized.

\n", "signature": "(self, _DatasetMean__context: Any):", "funcdef": "def"}, "bioimageio.core.stat_measures.DatasetMean.model_config": {"fullname": "bioimageio.core.stat_measures.DatasetMean.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMean.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.DatasetMean.model_fields": {"fullname": "bioimageio.core.stat_measures.DatasetMean.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMean.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True), 'scope': FieldInfo(annotation=Literal['dataset'], required=False, default='dataset'), 'name': FieldInfo(annotation=Literal['mean'], required=False, default='mean'), 'axes': FieldInfo(annotation=Union[Tuple[AxisId, ...], NoneType], required=False, default=None)}"}, "bioimageio.core.stat_measures.DatasetMean.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.DatasetMean.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMean.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.SampleStd": {"fullname": "bioimageio.core.stat_measures.SampleStd", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleStd", "kind": "class", "doc": "

The standard deviation of a single tensor

\n", "bases": "_Std, SampleMeasureBase"}, "bioimageio.core.stat_measures.SampleStd.compute": {"fullname": "bioimageio.core.stat_measures.SampleStd.compute", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleStd.compute", "kind": "function", "doc": "

compute the measure

\n", "signature": "(\tself,\tsample: bioimageio.core.stat_measures.SampleLike) -> Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]:", "funcdef": "def"}, "bioimageio.core.stat_measures.SampleStd.model_post_init": {"fullname": "bioimageio.core.stat_measures.SampleStd.model_post_init", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleStd.model_post_init", "kind": "function", "doc": "

Override this method to perform additional initialization after __init__ and model_construct.\nThis is useful if you want to do some validation that requires the entire model to be initialized.

\n", "signature": "(self, _SampleStd__context: Any):", "funcdef": "def"}, "bioimageio.core.stat_measures.SampleStd.model_config": {"fullname": "bioimageio.core.stat_measures.SampleStd.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleStd.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.SampleStd.model_fields": {"fullname": "bioimageio.core.stat_measures.SampleStd.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleStd.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True), 'scope': FieldInfo(annotation=Literal['sample'], required=False, default='sample'), 'name': FieldInfo(annotation=Literal['std'], required=False, default='std'), 'axes': FieldInfo(annotation=Union[Tuple[AxisId, ...], NoneType], required=False, default=None)}"}, "bioimageio.core.stat_measures.SampleStd.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.SampleStd.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleStd.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.DatasetStd": {"fullname": "bioimageio.core.stat_measures.DatasetStd", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetStd", "kind": "class", "doc": "

The standard deviation across multiple samples

\n", "bases": "_Std, DatasetMeasureBase"}, "bioimageio.core.stat_measures.DatasetStd.model_post_init": {"fullname": "bioimageio.core.stat_measures.DatasetStd.model_post_init", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetStd.model_post_init", "kind": "function", "doc": "

Override this method to perform additional initialization after __init__ and model_construct.\nThis is useful if you want to do some validation that requires the entire model to be initialized.

\n", "signature": "(self, _DatasetStd__context: Any):", "funcdef": "def"}, "bioimageio.core.stat_measures.DatasetStd.model_config": {"fullname": "bioimageio.core.stat_measures.DatasetStd.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetStd.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.DatasetStd.model_fields": {"fullname": "bioimageio.core.stat_measures.DatasetStd.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetStd.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True), 'scope': FieldInfo(annotation=Literal['dataset'], required=False, default='dataset'), 'name': FieldInfo(annotation=Literal['std'], required=False, default='std'), 'axes': FieldInfo(annotation=Union[Tuple[AxisId, ...], NoneType], required=False, default=None)}"}, "bioimageio.core.stat_measures.DatasetStd.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.DatasetStd.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetStd.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.SampleVar": {"fullname": "bioimageio.core.stat_measures.SampleVar", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleVar", "kind": "class", "doc": "

The variance of a single tensor

\n", "bases": "_Var, SampleMeasureBase"}, "bioimageio.core.stat_measures.SampleVar.compute": {"fullname": "bioimageio.core.stat_measures.SampleVar.compute", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleVar.compute", "kind": "function", "doc": "

compute the measure

\n", "signature": "(\tself,\tsample: bioimageio.core.stat_measures.SampleLike) -> Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]:", "funcdef": "def"}, "bioimageio.core.stat_measures.SampleVar.model_post_init": {"fullname": "bioimageio.core.stat_measures.SampleVar.model_post_init", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleVar.model_post_init", "kind": "function", "doc": "

Override this method to perform additional initialization after __init__ and model_construct.\nThis is useful if you want to do some validation that requires the entire model to be initialized.

\n", "signature": "(self, _SampleVar__context: Any):", "funcdef": "def"}, "bioimageio.core.stat_measures.SampleVar.model_config": {"fullname": "bioimageio.core.stat_measures.SampleVar.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleVar.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.SampleVar.model_fields": {"fullname": "bioimageio.core.stat_measures.SampleVar.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleVar.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True), 'scope': FieldInfo(annotation=Literal['sample'], required=False, default='sample'), 'name': FieldInfo(annotation=Literal['var'], required=False, default='var'), 'axes': FieldInfo(annotation=Union[Tuple[AxisId, ...], NoneType], required=False, default=None)}"}, "bioimageio.core.stat_measures.SampleVar.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.SampleVar.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleVar.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.DatasetVar": {"fullname": "bioimageio.core.stat_measures.DatasetVar", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetVar", "kind": "class", "doc": "

The variance across multiple samples

\n", "bases": "_Var, DatasetMeasureBase"}, "bioimageio.core.stat_measures.DatasetVar.model_post_init": {"fullname": "bioimageio.core.stat_measures.DatasetVar.model_post_init", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetVar.model_post_init", "kind": "function", "doc": "

Override this method to perform additional initialization after __init__ and model_construct.\nThis is useful if you want to do some validation that requires the entire model to be initialized.

\n", "signature": "(self, _DatasetVar__context: Any):", "funcdef": "def"}, "bioimageio.core.stat_measures.DatasetVar.model_config": {"fullname": "bioimageio.core.stat_measures.DatasetVar.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetVar.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.DatasetVar.model_fields": {"fullname": "bioimageio.core.stat_measures.DatasetVar.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetVar.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True), 'scope': FieldInfo(annotation=Literal['dataset'], required=False, default='dataset'), 'name': FieldInfo(annotation=Literal['var'], required=False, default='var'), 'axes': FieldInfo(annotation=Union[Tuple[AxisId, ...], NoneType], required=False, default=None)}"}, "bioimageio.core.stat_measures.DatasetVar.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.DatasetVar.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetVar.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.SampleQuantile": {"fullname": "bioimageio.core.stat_measures.SampleQuantile", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleQuantile", "kind": "class", "doc": "

The nth percentile of a single tensor

\n", "bases": "_Quantile, SampleMeasureBase"}, "bioimageio.core.stat_measures.SampleQuantile.compute": {"fullname": "bioimageio.core.stat_measures.SampleQuantile.compute", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleQuantile.compute", "kind": "function", "doc": "

compute the measure

\n", "signature": "(\tself,\tsample: bioimageio.core.stat_measures.SampleLike) -> Union[float, Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator at 0x7f163b23bec0>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer at 0x7f163b258220>, return_type=PydanticUndefined, when_used='always')]]:", "funcdef": "def"}, "bioimageio.core.stat_measures.SampleQuantile.model_post_init": {"fullname": "bioimageio.core.stat_measures.SampleQuantile.model_post_init", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleQuantile.model_post_init", "kind": "function", "doc": "

Override this method to perform additional initialization after __init__ and model_construct.\nThis is useful if you want to do some validation that requires the entire model to be initialized.

\n", "signature": "(self, _SampleQuantile__context: Any):", "funcdef": "def"}, "bioimageio.core.stat_measures.SampleQuantile.model_config": {"fullname": "bioimageio.core.stat_measures.SampleQuantile.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleQuantile.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.SampleQuantile.model_fields": {"fullname": "bioimageio.core.stat_measures.SampleQuantile.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleQuantile.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True), 'scope': FieldInfo(annotation=Literal['sample'], required=False, default='sample'), 'name': FieldInfo(annotation=Literal['quantile'], required=False, default='quantile'), 'q': FieldInfo(annotation=float, required=True), 'axes': FieldInfo(annotation=Union[Tuple[AxisId, ...], NoneType], required=False, default=None)}"}, "bioimageio.core.stat_measures.SampleQuantile.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.SampleQuantile.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleQuantile.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.DatasetPercentile": {"fullname": "bioimageio.core.stat_measures.DatasetPercentile", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetPercentile", "kind": "class", "doc": "

The nth percentile across multiple samples

\n", "bases": "_Quantile, DatasetMeasureBase"}, "bioimageio.core.stat_measures.DatasetPercentile.model_post_init": {"fullname": "bioimageio.core.stat_measures.DatasetPercentile.model_post_init", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetPercentile.model_post_init", "kind": "function", "doc": "

Override this method to perform additional initialization after __init__ and model_construct.\nThis is useful if you want to do some validation that requires the entire model to be initialized.

\n", "signature": "(self, _DatasetPercentile__context: Any):", "funcdef": "def"}, "bioimageio.core.stat_measures.DatasetPercentile.model_config": {"fullname": "bioimageio.core.stat_measures.DatasetPercentile.model_config", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetPercentile.model_config", "kind": "variable", "doc": "

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

\n", "annotation": ": ClassVar[pydantic.config.ConfigDict]", "default_value": "{'frozen': True}"}, "bioimageio.core.stat_measures.DatasetPercentile.model_fields": {"fullname": "bioimageio.core.stat_measures.DatasetPercentile.model_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetPercentile.model_fields", "kind": "variable", "doc": "

Metadata about the fields defined on the model,\nmapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

\n\n

This replaces Model.__fields__ from Pydantic V1.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.FieldInfo]]", "default_value": "{'member_id': FieldInfo(annotation=TensorId, required=True), 'scope': FieldInfo(annotation=Literal['dataset'], required=False, default='dataset'), 'name': FieldInfo(annotation=Literal['quantile'], required=False, default='quantile'), 'q': FieldInfo(annotation=float, required=True), 'axes': FieldInfo(annotation=Union[Tuple[AxisId, ...], NoneType], required=False, default=None)}"}, "bioimageio.core.stat_measures.DatasetPercentile.model_computed_fields": {"fullname": "bioimageio.core.stat_measures.DatasetPercentile.model_computed_fields", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetPercentile.model_computed_fields", "kind": "variable", "doc": "

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

\n", "annotation": ": ClassVar[Dict[str, pydantic.fields.ComputedFieldInfo]]", "default_value": "{}"}, "bioimageio.core.stat_measures.SampleMeasure": {"fullname": "bioimageio.core.stat_measures.SampleMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMeasure", "kind": "variable", "doc": "

\n", "default_value": "typing.Annotated[typing.Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]"}, "bioimageio.core.stat_measures.DatasetMeasure": {"fullname": "bioimageio.core.stat_measures.DatasetMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMeasure", "kind": "variable", "doc": "

\n", "default_value": "typing.Annotated[typing.Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]"}, "bioimageio.core.stat_measures.Measure": {"fullname": "bioimageio.core.stat_measures.Measure", "modulename": "bioimageio.core.stat_measures", "qualname": "Measure", "kind": "variable", "doc": "

\n", "default_value": "typing.Annotated[typing.Union[typing.Annotated[typing.Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)]"}, "bioimageio.core.stat_measures.Stat": {"fullname": "bioimageio.core.stat_measures.Stat", "modulename": "bioimageio.core.stat_measures", "qualname": "Stat", "kind": "variable", "doc": "

\n", "default_value": "typing.Dict[typing.Annotated[typing.Union[typing.Annotated[typing.Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='scope', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Union[float, typing.Annotated[bioimageio.core.tensor.Tensor, BeforeValidator(func=<function tensor_custom_before_validator>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function tensor_custom_serializer>, return_type=PydanticUndefined, when_used='always')]]]"}, "bioimageio.core.stat_measures.MeanMeasure": {"fullname": "bioimageio.core.stat_measures.MeanMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "MeanMeasure", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean]"}, "bioimageio.core.stat_measures.StdMeasure": {"fullname": "bioimageio.core.stat_measures.StdMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "StdMeasure", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd]"}, "bioimageio.core.stat_measures.VarMeasure": {"fullname": "bioimageio.core.stat_measures.VarMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "VarMeasure", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.DatasetVar]"}, "bioimageio.core.stat_measures.PercentileMeasure": {"fullname": "bioimageio.core.stat_measures.PercentileMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "PercentileMeasure", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile]"}, "bioimageio.core.tensor": {"fullname": "bioimageio.core.tensor", "modulename": "bioimageio.core.tensor", "kind": "module", "doc": "

\n"}, "bioimageio.core.tensor.Tensor": {"fullname": "bioimageio.core.tensor.Tensor", "modulename": "bioimageio.core.tensor", "qualname": "Tensor", "kind": "class", "doc": "

A wrapper around an xr.DataArray for better integration with bioimageio.spec\nand improved type annotations.

\n", "bases": "bioimageio.core._magic_tensor_ops.MagicTensorOpsMixin"}, "bioimageio.core.tensor.Tensor.__init__": {"fullname": "bioimageio.core.tensor.Tensor.__init__", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.__init__", "kind": "function", "doc": "

\n", "signature": "(\tarray: numpy.ndarray[typing.Any, numpy.dtype[typing.Any]],\tdims: Sequence[Union[bioimageio.spec.model.v0_5.AxisId, Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis]])"}, "bioimageio.core.tensor.Tensor.from_xarray": {"fullname": "bioimageio.core.tensor.Tensor.from_xarray", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.from_xarray", "kind": "function", "doc": "

create a Tensor from an xarray data array

\n\n

note for internal use: this factory method is round-trip save\n for any Tensor's data property (an xarray.DataArray).

\n", "signature": "(cls, data_array: xarray.core.dataarray.DataArray) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.from_numpy": {"fullname": "bioimageio.core.tensor.Tensor.from_numpy", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.from_numpy", "kind": "function", "doc": "

create a Tensor from a numpy array

\n\n

Args:\n array: the nd numpy array\n axes: A description of the array's axes,\n if None axes are guessed (which might fail and raise a ValueError.)

\n\n

Raises:\n ValueError: if axes is None and axes guessing fails.

\n", "signature": "(\tcls,\tarray: numpy.ndarray[typing.Any, numpy.dtype[typing.Any]],\t*,\tdims: Union[bioimageio.spec.model.v0_5.AxisId, Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis, Sequence[Union[bioimageio.spec.model.v0_5.AxisId, Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis]], NoneType]) -> bioimageio.core.tensor.Tensor:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.data": {"fullname": "bioimageio.core.tensor.Tensor.data", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.data", "kind": "variable", "doc": "

\n"}, "bioimageio.core.tensor.Tensor.dims": {"fullname": "bioimageio.core.tensor.Tensor.dims", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.dims", "kind": "variable", "doc": "

Tuple of dimension names associated with this tensor.

\n"}, "bioimageio.core.tensor.Tensor.tagged_shape": {"fullname": "bioimageio.core.tensor.Tensor.tagged_shape", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.tagged_shape", "kind": "variable", "doc": "

(alias for sizes) Ordered, immutable mapping from axis ids to lengths.

\n"}, "bioimageio.core.tensor.Tensor.shape_tuple": {"fullname": "bioimageio.core.tensor.Tensor.shape_tuple", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.shape_tuple", "kind": "variable", "doc": "

Tuple of tensor axes lengths

\n"}, "bioimageio.core.tensor.Tensor.size": {"fullname": "bioimageio.core.tensor.Tensor.size", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.size", "kind": "variable", "doc": "

Number of elements in the tensor.

\n\n

Equal to math.prod(tensor.shape), i.e., the product of the tensors\u2019 dimensions.

\n"}, "bioimageio.core.tensor.Tensor.sum": {"fullname": "bioimageio.core.tensor.Tensor.sum", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.sum", "kind": "function", "doc": "

Reduce this Tensor's data by applying sum along some dimension(s).

\n", "signature": "(\tself,\tdim: Union[bioimageio.spec.model.v0_5.AxisId, Sequence[bioimageio.spec.model.v0_5.AxisId], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.ndim": {"fullname": "bioimageio.core.tensor.Tensor.ndim", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.ndim", "kind": "variable", "doc": "

Number of tensor dimensions.

\n"}, "bioimageio.core.tensor.Tensor.dtype": {"fullname": "bioimageio.core.tensor.Tensor.dtype", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.dtype", "kind": "variable", "doc": "

\n", "annotation": ": Literal['bool', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64']"}, "bioimageio.core.tensor.Tensor.sizes": {"fullname": "bioimageio.core.tensor.Tensor.sizes", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.sizes", "kind": "variable", "doc": "

Ordered, immutable mapping from axis ids to axis lengths.

\n"}, "bioimageio.core.tensor.Tensor.astype": {"fullname": "bioimageio.core.tensor.Tensor.astype", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.astype", "kind": "function", "doc": "

Return tensor cast to dtype

\n\n

note: if dtype is already satisfied copy if copy

\n", "signature": "(\tself,\tdtype: Literal['bool', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64'],\t*,\tcopy: bool = False):", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.clip": {"fullname": "bioimageio.core.tensor.Tensor.clip", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.clip", "kind": "function", "doc": "

Return a tensor whose values are limited to [min, max].\nAt least one of max or min must be given.

\n", "signature": "(self, min: Optional[float] = None, max: Optional[float] = None):", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.crop_to": {"fullname": "bioimageio.core.tensor.Tensor.crop_to", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.crop_to", "kind": "function", "doc": "

crop to match sizes

\n", "signature": "(\tself,\tsizes: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\tcrop_where: Union[Literal['left', 'right', 'left_and_right'], Mapping[bioimageio.spec.model.v0_5.AxisId, Literal['left', 'right', 'left_and_right']]] = 'left_and_right') -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.expand_dims": {"fullname": "bioimageio.core.tensor.Tensor.expand_dims", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.expand_dims", "kind": "function", "doc": "

\n", "signature": "(\tself,\tdims: Union[Sequence[bioimageio.spec.model.v0_5.AxisId], Mapping[bioimageio.spec.model.v0_5.AxisId, int]]) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.mean": {"fullname": "bioimageio.core.tensor.Tensor.mean", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.mean", "kind": "function", "doc": "

\n", "signature": "(\tself,\tdim: Union[bioimageio.spec.model.v0_5.AxisId, Sequence[bioimageio.spec.model.v0_5.AxisId], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.std": {"fullname": "bioimageio.core.tensor.Tensor.std", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.std", "kind": "function", "doc": "

\n", "signature": "(\tself,\tdim: Union[bioimageio.spec.model.v0_5.AxisId, Sequence[bioimageio.spec.model.v0_5.AxisId], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.var": {"fullname": "bioimageio.core.tensor.Tensor.var", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.var", "kind": "function", "doc": "

\n", "signature": "(\tself,\tdim: Union[bioimageio.spec.model.v0_5.AxisId, Sequence[bioimageio.spec.model.v0_5.AxisId], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.pad": {"fullname": "bioimageio.core.tensor.Tensor.pad", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.pad", "kind": "function", "doc": "

\n", "signature": "(\tself,\tpad_width: Mapping[bioimageio.spec.model.v0_5.AxisId, Union[int, Tuple[int, int], bioimageio.core.common.PadWidth]],\tmode: Literal['edge', 'reflect', 'symmetric'] = 'symmetric') -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.pad_to": {"fullname": "bioimageio.core.tensor.Tensor.pad_to", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.pad_to", "kind": "function", "doc": "

pad tensor to match sizes

\n", "signature": "(\tself,\tsizes: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\tpad_where: Union[Literal['left', 'right', 'left_and_right'], Mapping[bioimageio.spec.model.v0_5.AxisId, Literal['left', 'right', 'left_and_right']]] = 'left_and_right',\tmode: Literal['edge', 'reflect', 'symmetric'] = 'symmetric') -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.quantile": {"fullname": "bioimageio.core.tensor.Tensor.quantile", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.quantile", "kind": "function", "doc": "

\n", "signature": "(\tself,\tq: Union[float, Sequence[float]],\tdim: Union[bioimageio.spec.model.v0_5.AxisId, Sequence[bioimageio.spec.model.v0_5.AxisId], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.resize_to": {"fullname": "bioimageio.core.tensor.Tensor.resize_to", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.resize_to", "kind": "function", "doc": "

return cropped/padded tensor with sizes

\n", "signature": "(\tself,\tsizes: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\t*,\tpad_where: Union[Literal['left', 'right', 'left_and_right'], Mapping[bioimageio.spec.model.v0_5.AxisId, Literal['left', 'right', 'left_and_right']]] = 'left_and_right',\tcrop_where: Union[Literal['left', 'right', 'left_and_right'], Mapping[bioimageio.spec.model.v0_5.AxisId, Literal['left', 'right', 'left_and_right']]] = 'left_and_right',\tpad_mode: Literal['edge', 'reflect', 'symmetric'] = 'symmetric'):", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.transpose": {"fullname": "bioimageio.core.tensor.Tensor.transpose", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.transpose", "kind": "function", "doc": "

return a transposed tensor

\n\n

Args:\n axes: the desired tensor axes

\n", "signature": "(self, axes: Sequence[bioimageio.spec.model.v0_5.AxisId]) -> Self:", "funcdef": "def"}, "bioimageio.core.utils": {"fullname": "bioimageio.core.utils", "modulename": "bioimageio.core.utils", "kind": "module", "doc": "

\n"}, "bioimageio.core.utils.testing": {"fullname": "bioimageio.core.utils.testing", "modulename": "bioimageio.core.utils.testing", "kind": "module", "doc": "

\n"}, "bioimageio.core.utils.testing.test_func": {"fullname": "bioimageio.core.utils.testing.test_func", "modulename": "bioimageio.core.utils.testing", "qualname": "test_func", "kind": "class", "doc": "

Base class for protocol classes.

\n\n

Protocol classes are defined as::

\n\n
class Proto(Protocol):\n    def meth(self) -> int:\n        ...\n
\n\n

Such classes are primarily used with static type checkers that recognize\nstructural subtyping (static duck-typing).

\n\n

For example::

\n\n
class C:\n    def meth(self) -> int:\n        return 0\n\ndef func(x: Proto) -> int:\n    return x.meth()\n\nfunc(C())  # Passes static type check\n
\n\n

See PEP 544 for details. Protocol classes decorated with\n@typing.runtime_checkable act as simple-minded runtime protocols that check\nonly the presence of given attributes, ignoring their type signatures.\nProtocol classes can be generic, they are defined as::

\n\n
class GenProto[T](Protocol):\n    def meth(self) -> T:\n        ...\n
\n", "bases": "typing.Protocol"}, "bioimageio.core.utils.testing.test_func.__init__": {"fullname": "bioimageio.core.utils.testing.test_func.__init__", "modulename": "bioimageio.core.utils.testing", "qualname": "test_func.__init__", "kind": "function", "doc": "

\n", "signature": "(*args, **kwargs)"}, "bioimageio.core.utils.testing.skip_on": {"fullname": "bioimageio.core.utils.testing.skip_on", "modulename": "bioimageio.core.utils.testing", "qualname": "skip_on", "kind": "function", "doc": "

adapted from https://stackoverflow.com/a/63522579

\n", "signature": "(exception: Type[Exception], reason: str):", "funcdef": "def"}, "bioimageio.core.weight_converter": {"fullname": "bioimageio.core.weight_converter", "modulename": "bioimageio.core.weight_converter", "kind": "module", "doc": "

coming soon

\n"}, "bioimageio.core.weight_converter.keras": {"fullname": "bioimageio.core.weight_converter.keras", "modulename": "bioimageio.core.weight_converter.keras", "kind": "module", "doc": "

\n"}, "bioimageio.core.weight_converter.torch": {"fullname": "bioimageio.core.weight_converter.torch", "modulename": "bioimageio.core.weight_converter.torch", "kind": "module", "doc": "

\n"}}, "docInfo": {"bioimageio.core": {"qualname": 0, "fullname": 2, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 2618}, "bioimageio.core.test_resource": {"qualname": 2, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 1282, "bases": 0, "doc": 16}, "bioimageio.core.load_resource": {"qualname": 2, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 1159, "bases": 0, "doc": 112}, "bioimageio.core.load_model": {"qualname": 2, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 567, "bases": 0, "doc": 22}, "bioimageio.core.axis": {"qualname": 0, "fullname": 3, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "bioimageio.core.axis.AxisId": {"qualname": 1, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 0, "bases": 5, "doc": 72}, "bioimageio.core.axis.AxisId.root_model": {"qualname": 3, "fullname": 6, "annotation": 5, "default_value": 17, "signature": 0, "bases": 0, "doc": 10}, 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