question about test

[luciaL]

Thank you for sharing.There are something wrong when i ran the "Demo_SR_Conv.m"in the test folder.The errors are listed below. Is there anything I need to set ?? 出错 VDSR_Matconvnet (line 15) convfea = vl_nnconv(im_y,weight{1},bias{1},'Pad',1);

出错 Demo_SR_Conv (line 49) im_h_y = VDSR_Matconvnet(im_l_y, model,up_scale,use_cascade);

[huangzehao]

Hi, have you installed matconvnet?

[cheongjunyoung]

Hello. First of all, thanks for your wonderful project. I have a question about the project. Have you tried to train VDSR model using matconvnet?? I have struggled with training it in matconvnet. There is no gradient clipping method in matconvnet so I clipped weight gradients using L2 norm. However, after training, PSNR result could not reach to even 32dB. this is my implementation of gradient clipping in matconvnet DAG version

T = net.params(p).der; clip = 1 / net.params(p).learningRate; norm = sqrt(sum(T(:).^2)); if norm>clip net.params(p).der = T*(clip/norm); end

I tried various clip values but all trained result were similar. I wish to know what different or problem are between my training method and Caffe. If you have any tips or comments, I would be glad. thank you

[huangzehao]

@cheongjunyoung Hi, I didn't trained VDSR using matconvnet. But I think you can simply implement gradient clip by a clamp-like function, like

grad(>threshold) = threshold
grad(<-threshold) = -threshold

You don't need to do gradient clipping like caffe. The purpose of gradient clipping is to overcome the problem of gradient explosion. Just clip big gradient to a certain value and you can handle this problem.

[luciaL]

I have installed matconvnet. It seems that I need to run setup before I run a new project. Thank you for your answering,I have a question about the training of multiple scale.How to train a model with {2,3}or{3,4}?Does it mean the input images are interpolated to different scale???

[huangzehao]

@luciaL Yes, but I didn't achieve better performance than single scale training. You can have a try.

[luciaL]

Okay，thank you.The input images are divided into the same size patches.Then the output images are also the same size patches.How to get the full image with the same scale factor??

[huangzehao]

It's the same with single scale training. I didn't achieve better performance in my experiments. Maybe you can ask the author of VDSR paper for help. Thanks.