Comments (3)
This issue arises with scikit-image = 0.19.x. The older version of skimage.transform.resize function converts the inputs from uint8 to an output of float64 and normalizes it within the function. But in the latest it produces an output of uint8 itself and does not normalize. So additional normalization of the mask is required so that it values are contained with 0s and 1s instead of a value of 255.
from brain-segmentation-pytorch.
Suggested changes:
def normalize_mask(mask):
mask = mask / (np.max(mask))
return mask
self.volumes = [(normalize_volume(v), normalize_mask(m)) for v, m in self.volumes]
from brain-segmentation-pytorch.
thanks!really useful !
from brain-segmentation-pytorch.
Related Issues (20)
- Reproducibility issue HOT 5
- how to train on my dataset HOT 5
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- dice
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from brain-segmentation-pytorch.