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car-detection-bayes
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loss lambda corrections

This commit is contained in:
Glenn Jocher 2018-09-13 14:15:49 +02:00
parent 9514e74438
commit 68de92f1a1
1 changed files with 4 additions and 4 deletions
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8
models.py
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@ -157,14 +157,14 @@ class YOLOLayer(nn.Module):
ly = 5 * MSELoss(y[mask], ty[mask])
lw = 5 * MSELoss(w[mask], tw[mask])
lh = 5 * MSELoss(h[mask], th[mask])
lconf = 1.5 * BCEWithLogitsLoss1(pred_conf[mask], mask[mask].float())
lconf = BCEWithLogitsLoss1(pred_conf[mask], mask[mask].float())
# lcls = nM * CrossEntropyLoss(pred_cls[mask], torch.argmax(tcls, 1))
lcls = nM * BCEWithLogitsLoss2(pred_cls[mask], tcls.float())
lcls = nM * CrossEntropyLoss(pred_cls[mask], torch.argmax(tcls, 1))
# lcls = nM * BCEWithLogitsLoss2(pred_cls[mask], tcls.float())
else:
lx, ly, lw, lh, lcls, lconf = FT([0]), FT([0]), FT([0]), FT([0]), FT([0]), FT([0])
lconf += nM * BCEWithLogitsLoss2(pred_conf[~mask], mask[~mask].float())
lconf += 0.5 * nM * BCEWithLogitsLoss2(pred_conf[~mask], mask[~mask].float())
loss = lx + ly + lw + lh + lconf + lcls