Li-Yun (James) Wang

When I ran mtcnn/data_preprocess/gen_Pnet_train_data.py, I received an error from this implementation. How did I resolve this issue? Thanks. Traceback (most recent call last): File "mtcnn/data_preprocess/gen_Pnet_train_data.py", line 162, in delta_x =...

@DantesDawn Hi, no, I could not solve this issue.

@DantesDawn Sounds great! I have not touched this code for a while because I was done with my internship (this code is part of my internship works). It is still...

@EdenBelouadah Thanks. No, I haven't. I will try it.

@capitaso Thank you for implementing NxN conv. However, in your implementation, there is a serious error where could not run "least_square_sklearn" because of 4 dimension inputs. Thanks,

@capitaso Sure. I tried to prune a pre-trained VGG16. I also added the following error message. Traceback (most recent call last): File "amc_search.py", line 233, in train(args.train_episode, agent, env, args.output)...

@capitaso The error was in the search phase. My plan is also going to prune the convolution layers. I believe the error is in the line "rec_weight = least_square_sklearn(X=masked_X, Y=Y)"...

I used a 3 by 3 kernel in that layer. Yeah. I agree with that.

@capitaso Sorry to reply to the message later. Sure. The following is the network architecture. vgg( (feature): Sequential( (0): Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (1): ReLU(inplace=True)...

@capitaso Thank you so much!! I will try the new one.