{"action":"closed","issue":{"url":"https://api.github.com/repos/Jack-CV/PCN/issues/3","repository_url":"https://api.github.com/repos/Jack-CV/PCN","labels_url":"https://api.github.com/repos/Jack-CV/PCN/issues/3/labels{/name}","comments_url":"https://api.github.com/repos/Jack-CV/PCN/issues/3/comments","events_url":"https://api.github.com/repos/Jack-CV/PCN/issues/3/events","html_url":"https://github.com/Jack-CV/PCN/issues/3","id":317225013,"number":3,"title":"Training Problem","user":{"login":"geyongtao","id":22744013,"avatar_url":"https://avatars0.githubusercontent.com/u/22744013?v=4","gravatar_id":"","url":"https://api.github.com/users/geyongtao","html_url":"https://github.com/geyongtao","followers_url":"https://api.github.com/users/geyongtao/followers","following_url":"https://api.github.com/users/geyongtao/following{/other_user}","gists_url":"https://api.github.com/users/geyongtao/gists{/gist_id}","starred_url":"https://api.github.com/users/geyongtao/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/geyongtao/subscriptions","organizations_url":"https://api.github.com/users/geyongtao/orgs","repos_url":"https://api.github.com/users/geyongtao/repos","events_url":"https://api.github.com/users/geyongtao/events{/privacy}","received_events_url":"https://api.github.com/users/geyongtao/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":1,"created_at":"2018-04-24T13:26:06Z","updated_at":"2018-04-25T16:00:56Z","closed_at":"2018-04-25T16:00:56Z","author_association":"NONE","body":"   Hi, @Jack-CV. It is really a nice work to detect the large pose face.  Can you explain how to get the rotate angular label of  face to supervise the trainning. As I know, WIDER FACE don't have the facial landmark. Do you use one of the facial landmark detect algorithms to get the facial landmark and then calculate the facial angular or just label all the faces manually?\r\n\r\nBesides, what do you mean that \"we rotate the initial training images uniformly in the range of...\" in section 2.3 and 2.4 of the paper?  As a beginner, I am confused of the statement."}}
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