Question about patchGAN

[SJTUzhanglj]

I read your paper and the implementation. The methods about patchGAN described in your paper seems promising, but how it is used in your code i wonder. You preprocess the data into patches before loading or some other way?

[ppwwyyxx]

patchGAN is still a convnet..
It's implemented in the code here.

[junyanz]

Yes, we use fully convolutional networks (FCN) as our disciminator, which is more efficient than patch-wise training/test. See here for more details about FCN.

[SJTUzhanglj]

Thanks for your quick reply.

[danmic]

@junyanz I was wondering how you get 70x70 patches using the configuration from the paper.

[phillipi]

As mentioned in #25, you can calculate the receptive field size of a layer using https://github.com/rbgirshick/rcnn/blob/master/utils/receptive_field_sizes.m.

[danmic]

@phillipi Thank you, it is clear now.

[programath]

@danmic Can you tell me how to get 70x70 result? I find the output size of discriminator is 30x30 and by using the equation mentioned above input_size=(output_size - 1)*stride+ksize, I just cannot get the correct result.

[phillipi]

@programath I modified the rcnn script to apply to our architecture:
https://github.com/phillipi/pix2pix/blob/master/scripts/receptive_field_sizes.m

You can see exactly how we calculate the receptive field sizes in that file. Please let me know if you see any issue with the calculation.

[phillipi]

What the n=1 discriminator means ?

"n" refers to the parameter n_layers in defineD_n_layers. Second, I think 1 output size in conv3 should project a receptive field in

the input with size 22 as follow: out = ... f(f(f(1, 4, 2), ... % conv2 -> conv3 4, 2), ... % conv1 -> conv2 4, 2); % input -> conv1 fprintf('conv3 receptive field size: %d\n', out); Am I right?

The last two convolutions (conv2 -> conv3 and conv1-> conv2) are both stride 1, rather than stride 2 as you have above. Setting it to stride 1, as in the receptive_field_sizes.m script, gives a receptive field of size 16.

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[xmyqsh]

So kindly of you! I've read the code and got it. Thanks a lot! 2017-04-23 6:39 GMT+08:00 Phillip Isola <notifications@github.com>:

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> What the n=1 discriminator means ? > "n" refers to the parameter n_layers in defineD_n_layers. Second, I think 1 output size in conv3 should project a receptive field in > the input with size 22 as follow: > > out = ... > f(f(f(1, 4, 2), ... % conv2 -> conv3 > 4, 2), ... % conv1 -> conv2 > 4, 2); % input -> conv1 > > fprintf('conv3 receptive field size: %d\n', out); > > Am I right? > The last two convolutions (conv2 -> conv3 and conv1-> conv2) are both stride 1, rather than stride 2 as you have above. Setting it to stride 1, as in the receptive_field_sizes.m script, gives a receptive field of size 16. > — > You are receiving this because you were mentioned. > Reply to this email directly, view it on GitHub > <#33 (comment)>, > or mute the thread > <https://github.com/notifications/unsubscribe-auth/ AAxoVsokzxdqa5nXgG9JjWqYSHAszFeZks5ryde2gaJpZM4LO5ha> > . > — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#33 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/APROTB97dcD6enSn9GIhtc_WXxm12Fzmks5ryoGZgaJpZM4LO5ha> .