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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-04-16 12:55:23 +02:00
parent b5ec9cb128
commit a8fb235647
1 changed files with 5 additions and 5 deletions
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10
utils/utils.py
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@ -263,14 +263,14 @@ def compute_loss(p, targets): # predictions, targets
pi = pi0[b, a, gj, gi] # predictions closest to anchors pi = pi0[b, a, gj, gi] # predictions closest to anchors
tconf[b, a, gj, gi] = 1 # conf tconf[b, a, gj, gi] = 1 # conf
lxy += (k * 0.07934) * MSE(torch.sigmoid(pi[..., 0:2]), txy[i]) # xy loss lxy += (k * 0.07997) * MSE(torch.sigmoid(pi[..., 0:2]), txy[i]) # xy loss
lwh += (k * 0.01561) * MSE(pi[..., 2:4], twh[i]) # wh yolo loss lwh += (k * 0.007867) * MSE(pi[..., 2:4], twh[i]) # wh yolo loss
# lwh += (k * 0.01561) * MSE(torch.sigmoid(pi[..., 2:4]), twh[i]) # wh power loss # lwh += (k * 0.007867) * MSE(torch.sigmoid(pi[..., 2:4]), twh[i]) # wh power loss
lcls += (k * 0.02094) * CE(pi[..., 5:], tcls[i]) # class_conf loss lcls += (k * 0.02111) * CE(pi[..., 5:], tcls[i]) # class_conf loss
# pos_weight = ft([gp[i] / min(gp) * 4.]) # pos_weight = ft([gp[i] / min(gp) * 4.])
# BCE = nn.BCEWithLogitsLoss(pos_weight=pos_weight) # BCE = nn.BCEWithLogitsLoss(pos_weight=pos_weight)
lconf += (k * 0.8841) * BCE(pi0[..., 4], tconf) # obj_conf loss lconf += (k * 0.8911) * BCE(pi0[..., 4], tconf) # obj_conf loss
loss = lxy + lwh + lconf + lcls loss = lxy + lwh + lconf + lcls
return loss, torch.cat((lxy, lwh, lconf, lcls, loss)).detach() return loss, torch.cat((lxy, lwh, lconf, lcls, loss)).detach()