faster-rcnn-pytorch-simple's People
faster-rcnn-pytorch-simple's Issues
Loss function - unpacked variables
Hey,
this project was really helpful to understand Faster R-CNN. So thanks :). But I think I found a small error that could contribute to lower performance.
In the loss calculation the pytorch-Variablefrcnn_bbox_pred
is unpacked and multiplied and after that casted to a Variable again:
frcnn_bbox_pred = to_var(torch.mul(frcnn_bbox_pred.data, frcnn_bbox_inside_weights))
To due this step .backward()
can not go further than this point. If you visualize the graph you will see it.
The following should work:
rcnn_bbox_inside_weights = torch.autograd.Variable(rcnn_bbox_inside_weights, requires_grad=False)
frcnn_bbox_pred = torch.mul(frcnn_bbox_pred, frcnn_bbox_inside_weights)
The same step is in the rpn_loss calculation.
Network issue
Hi @rimchang !
Thanks you a lot for this repo! Your repository helps me a lot in understanding the details Faster RCNN.
I found a small issue in your network define file here:
https://github.com/rimchang/Faster-RCNN-Pytorch-Simple/blob/master/FRCNN/model.py#L55
Do you miss the relu activation after convolution in RPN?
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