Merge branch 'main' into update-leaderboard

kaiko-ai · Oct 11, 2024 · 5ab619d · 5ab619d
2 parents 177356d + 26f38dd
commit 5ab619d
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Showing 8 changed files with 18 additions and 18 deletions.
diff --git a/configs/vision/pathology/offline/classification/camelyon16.yaml b/configs/vision/pathology/offline/classification/camelyon16.yaml
@@ -83,7 +83,7 @@ data:
           embeddings_transforms:
             class_path: eva.core.data.transforms.Pad2DTensor
             init_args:
-              pad_size: 10_000
+              pad_size: &N_PATCHES ${oc.env:N_PATCHES, 10000}
           target_transforms:
             class_path: eva.core.data.transforms.dtype.ArrayToFloatTensor
       val:
@@ -103,7 +103,7 @@ data:
             sampler:
               class_path: eva.vision.data.wsi.patching.samplers.ForegroundGridSampler
               init_args:
-                max_samples: 10_000
+                max_samples: *N_PATCHES
             width: 224
             height: 224
             target_mpp: 0.25

diff --git a/configs/vision/pathology/offline/classification/camelyon16_small.yaml b/configs/vision/pathology/offline/classification/camelyon16_small.yaml
@@ -83,7 +83,7 @@ data:
           embeddings_transforms:
             class_path: eva.core.data.transforms.Pad2DTensor
             init_args:
-              pad_size: &N_PATCHES 500
+              pad_size: &N_PATCHES ${oc.env:N_PATCHES, 1000}
           target_transforms:
             class_path: eva.core.data.transforms.dtype.ArrayToFloatTensor
       val:

diff --git a/configs/vision/pathology/offline/classification/panda.yaml b/configs/vision/pathology/offline/classification/panda.yaml
@@ -84,7 +84,7 @@ data:
           embeddings_transforms:
             class_path: eva.core.data.transforms.Pad2DTensor
             init_args:
-              pad_size: &N_PATCHES 1000
+              pad_size: &N_PATCHES ${oc.env:N_PATCHES, 1000}
       val:
         class_path: eva.datasets.MultiEmbeddingsClassificationDataset
         init_args:

diff --git a/configs/vision/pathology/offline/classification/panda_small.yaml b/configs/vision/pathology/offline/classification/panda_small.yaml
@@ -84,7 +84,7 @@ data:
           embeddings_transforms:
             class_path: eva.core.data.transforms.Pad2DTensor
             init_args:
-              pad_size: &N_PATCHES 200
+              pad_size: &N_PATCHES ${oc.env:N_PATCHES, 200}
       val:
         class_path: eva.datasets.MultiEmbeddingsClassificationDataset
         init_args:

diff --git a/configs/vision/pathology/offline/segmentation/monusac.yaml b/configs/vision/pathology/offline/segmentation/monusac.yaml
@@ -63,7 +63,7 @@ model:
       init_args:
         softmax: true
         batch: true
-        ignore_index: &IGNORE_INDEX 255
+        ignore_index: &IGNORE_INDEX 5
     optimizer:
       class_path: torch.optim.AdamW
       init_args:
@@ -84,17 +84,17 @@ model:
       evaluation:
         - class_path: eva.vision.metrics.defaults.MulticlassSegmentationMetrics
           init_args:
-            num_classes: *NUM_CLASSES
+            num_classes: 6
             ignore_index: *IGNORE_INDEX
         - class_path: torchmetrics.ClasswiseWrapper
           init_args:
             metric:
               class_path: eva.vision.metrics.GeneralizedDiceScore
               init_args:
-                num_classes: *NUM_CLASSES
+                num_classes: 6
                 weight_type: linear
-                per_class: true
                 ignore_index: *IGNORE_INDEX
+                per_class: true
 data:
   class_path: eva.DataModule
   init_args:

diff --git a/configs/vision/pathology/online/segmentation/monusac.yaml b/configs/vision/pathology/online/segmentation/monusac.yaml
@@ -54,7 +54,7 @@ model:
       init_args:
         softmax: true
         batch: true
-        ignore_index: &IGNORE_INDEX 255
+        ignore_index: &IGNORE_INDEX 5
     lr_multiplier_encoder: 0.0
     optimizer:
       class_path: torch.optim.AdamW
@@ -76,14 +76,14 @@ model:
       evaluation:
         - class_path: eva.vision.metrics.defaults.MulticlassSegmentationMetrics
           init_args:
-            num_classes: *NUM_CLASSES
+            num_classes: 6
             ignore_index: *IGNORE_INDEX
         - class_path: torchmetrics.ClasswiseWrapper
           init_args:
             metric:
               class_path: eva.vision.metrics.GeneralizedDiceScore
               init_args:
-                num_classes: *NUM_CLASSES
+                num_classes: 6
                 weight_type: linear
                 ignore_index: *IGNORE_INDEX
                 per_class: true

diff --git a/src/eva/core/models/transforms/extract_patch_features.py b/src/eva/core/models/transforms/extract_patch_features.py
@@ -37,7 +37,7 @@ def __call__(
             height = width = int(math.sqrt(patch_grid))
             if height * width != patch_grid:
                 if self._ignore_remaining_dims:
-                    features = features[:, :, : height * width]
+                    features = features[:, :, -height * width :]
                 else:
                     raise ValueError(f"Patch grid size must be a square number {patch_grid}.")
             patch_embeddings = features.view(batch_size, hidden_size, height, width)

diff --git a/src/eva/vision/data/datasets/segmentation/monusac.py b/src/eva/vision/data/datasets/segmentation/monusac.py
@@ -84,7 +84,7 @@ def __init__(
     @property
     @override
     def classes(self) -> List[str]:
-        return ["Epithelial", "Lymphocyte", "Neutrophil", "Macrophage"]
+        return ["Background", "Epithelial", "Lymphocyte", "Neutrophil", "Macrophage", "Ambiguous"]
 
     @functools.cached_property
     @override
@@ -107,8 +107,8 @@ def validate(self) -> None:
         _validators.check_dataset_integrity(
             self,
             length=self._expected_dataset_lengths.get(self._split, 0),
-            n_classes=4,
-            first_and_last_labels=("Epithelial", "Macrophage"),
+            n_classes=6,
+            first_and_last_labels=("Background", "Ambiguous"),
         )
 
     @override
@@ -199,9 +199,9 @@ def _get_semantic_mask(self, index: int) -> npt.NDArray[Any]:
         semantic_labels = np.zeros((height, width), "uint8")  # type: ignore[reportCallIssue]
         for level in range(len(root)):
             label = [item.attrib["Name"] for item in root[level][0]][0]
-            class_id = self.class_to_idx.get(label, 254) + 1
+            class_id = self.class_to_idx.get(label, self.class_to_idx["Ambiguous"])
             # for the test dataset an additional class 'Ambiguous' was added for
-            # difficult regions with fuzzy boundaries - we return it as 255
+            # difficult regions with fuzzy boundaries
             regions = [item for child in root[level] for item in child if item.tag == "Region"]
             for region in regions:
                 vertices = np.array(