Hi,
I am using MxNet 1.51 and GluonCv 0.4. Faster RCNN model from GluonCV model zoo returns by default the arrays `ids, scores, bboxes`. But instead of getting only the id and the score of the best scoring class, I want to get the the whole array with the scores for all classes. By inspecting the source code and in an ideal scenario, I would create a class that inherits from the `FasterRCNN` class and implement a method that is equal to hybrid_forward, but with a modified `nms` algorithm that would propagate the respective rows from `F.softmax(cls_pred, axis=-1)`. Since I do not have enough time, I am trying to add this function directly on the source code. But I have a problem, the hybrid_forward is defined as: `def hybrid_forward(self, F, x, gt_box=None):` There is this extra `F` parameter, that seems to be a module. What I do not understand is that, being `net` an instance of `FasterRCNN` and `x` an input tensor, I can get the output as: `ids, scores, bboxes = net(x)` With no extra parameter. Also, I have not found a modified `__call__` function for the FasterRCNN class that would deal with the `F`. Is this the right way to approach this problem? --- [Visit Topic](https://discuss.mxnet.io/t/understanding-and-modifying-faster-rcnn/6362/1) or reply to this email to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.mxnet.io/email/unsubscribe/b423615e993aeb7fd0a595d594b018c72f5f0ec4d619854aabbd0b8df9cf1a5d).
