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Division by thresholds first does have a very small chance to change the following argmax results.
e.g. A pixel with 2 classes has softmax result as [0.89, 0.11], but the thresholds so happens to be [0.9, 0.09], then it will satisfy weighted_prob > 1, but it is not even predicted as class 2.
Maybe this is indeed the original intent of the paper, but I'll just point it out here.
I call this minor problem because the example above is very unlikely to happen in actual training.
The text was updated successfully, but these errors were encountered:
CRST/crst_seg.py
Line 663 in 0374db8
Division by thresholds first does have a very small chance to change the following argmax results.
e.g. A pixel with 2 classes has softmax result as [0.89, 0.11], but the thresholds so happens to be [0.9, 0.09], then it will satisfy weighted_prob > 1, but it is not even predicted as class 2.
Maybe this is indeed the original intent of the paper, but I'll just point it out here.
I call this minor problem because the example above is very unlikely to happen in actual training.
The text was updated successfully, but these errors were encountered: