{"action":"created","issue":{"url":"https://api.github.com/repos/junyanz/pytorch-CycleGAN-and-pix2pix/issues/302","repository_url":"https://api.github.com/repos/junyanz/pytorch-CycleGAN-and-pix2pix","labels_url":"https://api.github.com/repos/junyanz/pytorch-CycleGAN-and-pix2pix/issues/302/labels{/name}","comments_url":"https://api.github.com/repos/junyanz/pytorch-CycleGAN-and-pix2pix/issues/302/comments","events_url":"https://api.github.com/repos/junyanz/pytorch-CycleGAN-and-pix2pix/issues/302/events","html_url":"https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix/issues/302","id":334360076,"node_id":"MDU6SXNzdWUzMzQzNjAwNzY=","number":302,"title":"The dataloader for the pix2pix?Can you help me?","user":{"login":"tangjilin","id":35884085,"node_id":"MDQ6VXNlcjM1ODg0MDg1","avatar_url":"https://avatars1.githubusercontent.com/u/35884085?v=4","gravatar_id":"","url":"https://api.github.com/users/tangjilin","html_url":"https://github.com/tangjilin","followers_url":"https://api.github.com/users/tangjilin/followers","following_url":"https://api.github.com/users/tangjilin/following{/other_user}","gists_url":"https://api.github.com/users/tangjilin/gists{/gist_id}","starred_url":"https://api.github.com/users/tangjilin/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/tangjilin/subscriptions","organizations_url":"https://api.github.com/users/tangjilin/orgs","repos_url":"https://api.github.com/users/tangjilin/repos","events_url":"https://api.github.com/users/tangjilin/events{/privacy}","received_events_url":"https://api.github.com/users/tangjilin/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":9,"created_at":"2018-06-21T06:49:18Z","updated_at":"2019-11-03T16:39:20Z","closed_at":"2018-06-28T05:55:28Z","author_association":"NONE","body":"Hello！The model I use is Pix2Pix.  \r\nWhat I want to achieve is : given a RGB image A and a label image B , I want to generate a new RGB image C (corresponding to the label B). In other words ,the input is the stack of A and B, the output is C. However ,in the paper, the input and output is the same channel(3 channels RGB). So what should I do to modify the Dataloader or how should I do to apply my form of input to the Pix2Pix model?Thanks in advance!"},"comment":{"url":"https://api.github.com/repos/junyanz/pytorch-CycleGAN-and-pix2pix/issues/comments/549155550","html_url":"https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix/issues/302#issuecomment-549155550","issue_url":"https://api.github.com/repos/junyanz/pytorch-CycleGAN-and-pix2pix/issues/302","id":549155550,"node_id":"MDEyOklzc3VlQ29tbWVudDU0OTE1NTU1MA==","user":{"login":"gd1925","id":50822928,"node_id":"MDQ6VXNlcjUwODIyOTI4","avatar_url":"https://avatars2.githubusercontent.com/u/50822928?v=4","gravatar_id":"","url":"https://api.github.com/users/gd1925","html_url":"https://github.com/gd1925","followers_url":"https://api.github.com/users/gd1925/followers","following_url":"https://api.github.com/users/gd1925/following{/other_user}","gists_url":"https://api.github.com/users/gd1925/gists{/gist_id}","starred_url":"https://api.github.com/users/gd1925/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/gd1925/subscriptions","organizations_url":"https://api.github.com/users/gd1925/orgs","repos_url":"https://api.github.com/users/gd1925/repos","events_url":"https://api.github.com/users/gd1925/events{/privacy}","received_events_url":"https://api.github.com/users/gd1925/received_events","type":"User","site_admin":false},"created_at":"2019-11-03T16:39:20Z","updated_at":"2019-11-03T16:39:20Z","author_association":"NONE","body":"Hello Sir,\r\nFirstly I am extremely sorry for the delayed response. I had thought I would reply after I figure out the next steps. But I haven't been able to do it. Sir, I have some trouble with using the transformation of images. I understand that I have to transform them to tensors and then return the paths to A and B. In my case I have 4-Channel stacked input and 3-Channel output. I tried using `# dataA = ToTensor()(A) # dataB = ToTensor()(B)` and also these - `params = get_params(self.opt, B.size)\r\ndataA = get_transform(self.opt, params, method=Image.BILINEAR, normalize=False)\r\ndataB = get_transform(self.opt, params)` and ` transform_params = get_params(self.opt, A.size)\r\n        A_transform = get_transform(self.opt, transform_params, grayscale=(self.input_nc == 1))\r\n        B_transform = get_transform(self.opt, transform_params, grayscale=(self.output_nc == 1))`. But I run into runtime errors. I was trying to apply the same transformations on both the images. Is my understanding correct?\r\n\r\nOnce again, I apologize for the delay. I am very thankful for your time and consideration so far."}}
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