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class ComputeLoss: # Compute losses def init(self, model, autobalance=False): super(ComputeLoss, self).init() device = next(model.parameters()).device # get model device h = model.hyp # hyperparameters
# Define criteria BCEcls = nn.BCEWithLogitsLoss(pos_weight=torch.tensor([h['cls_pw']], device=device)) BCEobj = nn.BCEWithLogitsLoss(pos_weight=torch.tensor([h['obj_pw']], device=device))
The text was updated successfully, but these errors were encountered:
BCEobj for object or background, when there is a object, BCEcls for object's class. You can review Yolo's design.
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class ComputeLoss:
# Compute losses
def init(self, model, autobalance=False):
super(ComputeLoss, self).init()
device = next(model.parameters()).device # get model device
h = model.hyp # hyperparameters
The text was updated successfully, but these errors were encountered: