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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2018-09-10 17:02:38 +02:00
parent a8f8ec134b
commit 9514e74438
1 changed files with 4 additions and 2 deletions
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6
models.py
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@ -159,14 +159,16 @@ class YOLOLayer(nn.Module):
lh = 5 * MSELoss(h[mask], th[mask])
lconf = 1.5 * 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())
loss = lx + ly + lw + lh + lconf + lcls
# Sum False Positives from unnasigned anchors
i = torch.sigmoid(pred_conf[~mask]) > 0.99
FPe = torch.zeros(self.nC)
if i.sum() > 0: