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semseg = mask_cls.softmax(-1) @ mask_pred.sigmoid()
which will result in: 1>= semseg >= 0
When we compute loss_func, we set semseg as a logits, and compute prob by semseg.sigmoid()
If 1>= semseg >= 0,the probs must be >= 0.5, but we need the prob >=0.
Maybe I am wrong or I miss some calculation process,please feel free to advise me。
The text was updated successfully, but these errors were encountered:
SegVit/decode_heads/atm_single_head.py
Line 277 in 8561638
semseg = mask_cls.softmax(-1) @ mask_pred.sigmoid()
which will result in: 1>= semseg >= 0
When we compute loss_func, we set semseg as a logits, and compute prob by semseg.sigmoid()
If 1>= semseg >= 0,the probs must be >= 0.5, but we need the prob >=0.
Maybe I am wrong or I miss some calculation process,please feel free to advise me。
The text was updated successfully, but these errors were encountered: