Hi there,
thanks for your code, its very useful!
I was trying to understand how bbox_pred affects the RoI, if it affects it at all? I can see that rpn_bbox_pred affects the RoIs through self._proposal_layer(rpn_cls_prob, rpn_bbox_pred, "rois"). However, I don't see something similar for bbox_pred. Why are we calculating the loss for this variable if doesn't affect the RoI during training?
Hi there, thanks for your code, its very useful! I was trying to understand how bbox_pred affects the RoI, if it affects it at all? I can see that rpn_bbox_pred affects the RoIs through self._proposal_layer(rpn_cls_prob, rpn_bbox_pred, "rois"). However, I don't see something similar for bbox_pred. Why are we calculating the loss for this variable if doesn't affect the RoI during training?