updates
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@@ -324,6 +324,14 @@ def compute_loss(p, targets, model, giou_loss=True): # predictions, targets, mo
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lcls += (k * h['cls']) * BCEcls(pi[..., 5:], tclsm) # BCE
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# lcls += (k * h['cls']) * CE(pi[..., 5:], tcls[i]) # CE
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# udm_ce = torch.zeros_like(pi0[..., 0]).long() # unified detection matrix for CE
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# udm_ce[b, a, gj, gi] = tcls[i] + 1
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# lcls += (k * h['cls']) * CE(pi0[..., 4:].view(-1, model.nc + 1), udm_ce.view(-1)) # unified CE
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# udm = torch.zeros_like(pi0[..., 5:]) # unified detection matrix for BCE
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# udm[b, a, gj, gi, tcls[i]] = 1.0
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# lcls += (k * h['cls']) * BCEcls(pi0[..., 5:], udm) # unified BCE (hyps 200-30)
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# Append targets to text file
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# with open('targets.txt', 'a') as file:
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# [file.write('%11.5g ' * 4 % tuple(x) + '\n') for x in torch.cat((txy[i], twh[i]), 1)]
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