{"action":"closed","issue":{"url":"https://api.github.com/repos/titu1994/Super-Resolution-using-Generative-Adversarial-Networks/issues/6","repository_url":"https://api.github.com/repos/titu1994/Super-Resolution-using-Generative-Adversarial-Networks","labels_url":"https://api.github.com/repos/titu1994/Super-Resolution-using-Generative-Adversarial-Networks/issues/6/labels{/name}","comments_url":"https://api.github.com/repos/titu1994/Super-Resolution-using-Generative-Adversarial-Networks/issues/6/comments","events_url":"https://api.github.com/repos/titu1994/Super-Resolution-using-Generative-Adversarial-Networks/issues/6/events","html_url":"https://github.com/titu1994/Super-Resolution-using-Generative-Adversarial-Networks/issues/6","id":188399262,"number":6,"title":"how to ready for training data?","user":{"login":"eeric","id":8744274,"avatar_url":"https://avatars.githubusercontent.com/u/8744274?v=3","gravatar_id":"","url":"https://api.github.com/users/eeric","html_url":"https://github.com/eeric","followers_url":"https://api.github.com/users/eeric/followers","following_url":"https://api.github.com/users/eeric/following{/other_user}","gists_url":"https://api.github.com/users/eeric/gists{/gist_id}","starred_url":"https://api.github.com/users/eeric/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/eeric/subscriptions","organizations_url":"https://api.github.com/users/eeric/orgs","repos_url":"https://api.github.com/users/eeric/repos","events_url":"https://api.github.com/users/eeric/events{/privacy}","received_events_url":"https://api.github.com/users/eeric/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":7,"created_at":"2016-11-10T01:42:05Z","updated_at":"2016-11-12T07:21:21Z","closed_at":"2016-11-12T07:21:21Z","body":"1.Training Details and Parameters is as the paper: Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network, is it?\r\n\r\n2.the bicubic kernel is for bicubic interpolation when making the training data, does it?\r\n\r\n"}}
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