Comments (2)
If your model had not been well trained, the post-processing steps could be very time consuming because there are some loops on positive predictions. And therefore, It can be speculated that you focal loss model was poorly trained.
Firstly, I see that you are using sigmoid as the probability output function, have you modified the net structure as well, since I used softmax instead.
Secondly, the focal loss has alpha, gamma as its hyper parameters, have you tried and find a good combination for this task?
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It's awesome of you.I never thought that poor trained model can lead to this problem..
Thank you very much!
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Related Issues (20)
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