{"action":"created","issue":{"url":"https://api.github.com/repos/AlfredXiangWu/face_verification_experiment/issues/3","labels_url":"https://api.github.com/repos/AlfredXiangWu/face_verification_experiment/issues/3/labels{/name}","comments_url":"https://api.github.com/repos/AlfredXiangWu/face_verification_experiment/issues/3/comments","events_url":"https://api.github.com/repos/AlfredXiangWu/face_verification_experiment/issues/3/events","html_url":"https://github.com/AlfredXiangWu/face_verification_experiment/issues/3","id":94621795,"number":3,"title":"feature dimension","user":{"login":"kingloo2014","id":8522647,"avatar_url":"https://avatars.githubusercontent.com/u/8522647?v=3","gravatar_id":"","url":"https://api.github.com/users/kingloo2014","html_url":"https://github.com/kingloo2014","followers_url":"https://api.github.com/users/kingloo2014/followers","following_url":"https://api.github.com/users/kingloo2014/following{/other_user}","gists_url":"https://api.github.com/users/kingloo2014/gists{/gist_id}","starred_url":"https://api.github.com/users/kingloo2014/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/kingloo2014/subscriptions","organizations_url":"https://api.github.com/users/kingloo2014/orgs","repos_url":"https://api.github.com/users/kingloo2014/repos","events_url":"https://api.github.com/users/kingloo2014/events{/privacy}","received_events_url":"https://api.github.com/users/kingloo2014/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"milestone":null,"comments":5,"created_at":"2015-07-13T02:15:19Z","updated_at":"2015-08-04T09:51:36Z","closed_at":"2015-07-15T07:53:48Z","body":"Hi, why the features stored in the matlab matrix is 256 dimensions? but fc1-layer in the network's output number is 512. I cannot understand which layer's output treat as the terminal feature!"},"comment":{"url":"https://api.github.com/repos/AlfredXiangWu/face_verification_experiment/issues/comments/127548977","html_url":"https://github.com/AlfredXiangWu/face_verification_experiment/issues/3#issuecomment-127548977","issue_url":"https://api.github.com/repos/AlfredXiangWu/face_verification_experiment/issues/3","id":127548977,"user":{"login":"kingloo2014","id":8522647,"avatar_url":"https://avatars.githubusercontent.com/u/8522647?v=3","gravatar_id":"","url":"https://api.github.com/users/kingloo2014","html_url":"https://github.com/kingloo2014","followers_url":"https://api.github.com/users/kingloo2014/followers","following_url":"https://api.github.com/users/kingloo2014/following{/other_user}","gists_url":"https://api.github.com/users/kingloo2014/gists{/gist_id}","starred_url":"https://api.github.com/users/kingloo2014/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/kingloo2014/subscriptions","organizations_url":"https://api.github.com/users/kingloo2014/orgs","repos_url":"https://api.github.com/users/kingloo2014/repos","events_url":"https://api.github.com/users/kingloo2014/events{/privacy}","received_events_url":"https://api.github.com/users/kingloo2014/received_events","type":"User","site_admin":false},"created_at":"2015-08-04T09:51:36Z","updated_at":"2015-08-04T09:51:36Z","body":"hello，I'm sorry to disturb you again. Three problem need to consult you.\n1.I want to know how to prepare the training samples. The input layer of the model is the pair of face images or a single face image? \n2.And your validated samples are the same source with the training samples? \n3.If I resize the aligned face smaller, the test result will be same as your result?\n----- 原始邮件 -----\n发件人：Alfred Xiang Wu <notifications@github.com>\n收件人：AlfredXiangWu/face_verification_experiment <face_verification_experiment@noreply.github.com>\n抄送人：kingloo2014 <kinglord2006@sina.com>\n主题：Re: [face_verification_experiment] feature dimension (#3)\n日期：2015年07月13日 16点32分\n\nlayers {\n\r\n  name: \"data\"\n\r\n  type:DATA\n\r\n  top: \"data\"\n\r\n  top: \"label\"\n\r\n  data_param{\n\r\n      source: \"/mnt/wuxiang/User/team01/data/lmdb/CASIA_WebFace_align_3_train_lmdb\"\n\r\n      backend: LMDB\n\r\n      batch_size: 64\n\r\n    }\n\r\n  transform_param {\n\r\n    scale: 0.00390625\n\r\n    crop_size: 128\n\r\n    mirror: true\n\r\n  }\n\r\n  include: { phase: TRAIN }\n\r\n}\r\n\r\nAs is shown in \"transform_param\", the crop_size is set to 128, which means the inputs of CNN are cropped from 144x144 to 128x128 randomly for training. This data augmentation trick is widely used in ILSVRC competition. Therefore, the real input of CNN is 128, and the test image is resized to 128x128. \r\n\r\n&mdash;\nReply to this email directly or view it on GitHub.\r\n\r\n  \r\n    \r\n    \r\n  \r\n  \r\n\r\n\r\n"}}