Improving image io #2079
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Improving image io #2079
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ancestor-mithril
commented
Apr 11, 2024
ancestor-mithril
commented
- reducing the number of allocations when reading images and writing segmentations
- segmentation are casted to np.uint8 only if they are not already np.uint8
- images are stacked directly into a float32 array, without additional casts
* reducing the number of allocations when reading images and writing segmentations * segmentation are casted to np.uint8 only if they are not already np.uint8 * images are stacked directly into a float32 array, without additional casts
| @@ -56,13 +56,13 @@ def read_images(self, image_fnames: Union[List[str], Tuple[str, ...]]) -> Tuple[ | |||
| print('Image files:') | |||
| print(image_fnames) | |||
| raise RuntimeError() | |||
| return np.vstack(images).astype(np.float32), {'spacing': (999, 1, 1)} | |||
| return np.vstack(images, dtype=np.float32, casting='unsafe'), {'spacing': (999, 1, 1)} | |||
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Can you comment on the use of 'unsafe', any specific reason this is picked?
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I've chosen 'unsafe' for backwards compatibility as astype uses 'unsafe' casting (https://numpy.org/doc/stable/reference/generated/numpy.ndarray.astype.html).
Moreover, 'unsafe' casting is needed in this case because numpy raises an exception when casting from int32 to float32:
>>> import numpy as np
>>> x = np.array([1, 2, 3], dtype=np.int32)
>>> x.astype(np.float32)
array([1., 2., 3.], dtype=float32)
>>> x.astype(np.float32, casting='safe')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: Cannot cast array data from dtype('int32') to dtype('float32') according to the rule 'safe'
|
Thanks! |
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