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Change image_utils.py to work with nnunetv2 predictions and ground truth labels with multi-class segmentations. #17

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merged 8 commits into from
May 6, 2024
Merged

Change image_utils.py to work with nnunetv2 predictions and ground truth labels with multi-class segmentations. #17

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fd5eb55
Update image_utils.py
NataliaAlves13 Apr 23, 2024
e65ca44
update image_utils.py to work with nnunetv2
NataliaAlves13 Apr 23, 2024
b7ffe03
fix coding style issues
NataliaAlves13 Apr 23, 2024
4b402c9
Update image_utils.py
NataliaAlves13 Apr 23, 2024
d70ac90
fix formatting
NataliaAlves13 Apr 23, 2024
b4518b2
Update image_utils.py
NataliaAlves13 Apr 23, 2024
d7260f1
Update image_utils.py
NataliaAlves13 Apr 23, 2024
1ac6d83
Update supported Python versions
joeranbosma May 6, 2024
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6 changes: 5 additions & 1 deletion src/picai_eval/image_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -69,7 +69,10 @@ def read_image(path: PathLike):
elif '.nii' in path or '.mha' in path or 'mhd' in path:
return sitk.GetArrayFromImage(sitk.ReadImage(path))
elif '.npz' in path:
return np.load(path)['softmax'].astype('float32')[1] # nnUnet format
try:
return np.load(path)['softmax'].astype('float32')[1] # nnUnet format
except:
return np.load(path)['probabilities'].astype('float32')[1] # nnUnet format
else:
raise ValueError(f"Unexpected file path. Supported file formats: .nii(.gz), .mha, .npy and .npz. Got: {path}.")

Expand All @@ -85,4 +88,5 @@ def read_label(path: PathLike) -> "npt.NDArray[np.int32]":
"""Read label, given a filepath"""
# read label and ensure correct dtype
lbl: "npt.NDArray[np.int32]" = np.array(read_image(path), dtype=np.int32)
lbl[lbl!=1]=0
return lbl
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