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Avoid obtaining NaN loss value during training #69

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Avoid obtaining NaN loss value during training #69

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2 changes: 1 addition & 1 deletion pytorch_iou/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@ def _iou(pred, target, size_average = True):
for i in range(0,b):
#compute the IoU of the foreground
Iand1 = torch.sum(target[i,:,:,:]*pred[i,:,:,:])
Ior1 = torch.sum(target[i,:,:,:]) + torch.sum(pred[i,:,:,:])-Iand1
Ior1 = torch.sum(target[i,:,:,:]) + torch.sum(pred[i,:,:,:])-Iand1 + 1e-6
IoU1 = Iand1/Ior1

#IoU loss is (1-IoU1)
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