{"action":"closed","issue":{"url":"https://api.github.com/repos/xingyizhou/pytorch-pose-hg-3d/issues/21","repository_url":"https://api.github.com/repos/xingyizhou/pytorch-pose-hg-3d","labels_url":"https://api.github.com/repos/xingyizhou/pytorch-pose-hg-3d/issues/21/labels{/name}","comments_url":"https://api.github.com/repos/xingyizhou/pytorch-pose-hg-3d/issues/21/comments","events_url":"https://api.github.com/repos/xingyizhou/pytorch-pose-hg-3d/issues/21/events","html_url":"https://github.com/xingyizhou/pytorch-pose-hg-3d/issues/21","id":330642693,"node_id":"MDU6SXNzdWUzMzA2NDI2OTM=","number":21,"title":"Some questions about train-set","user":{"login":"salihkaragoz","id":22906895,"node_id":"MDQ6VXNlcjIyOTA2ODk1","avatar_url":"https://avatars0.githubusercontent.com/u/22906895?v=4","gravatar_id":"","url":"https://api.github.com/users/salihkaragoz","html_url":"https://github.com/salihkaragoz","followers_url":"https://api.github.com/users/salihkaragoz/followers","following_url":"https://api.github.com/users/salihkaragoz/following{/other_user}","gists_url":"https://api.github.com/users/salihkaragoz/gists{/gist_id}","starred_url":"https://api.github.com/users/salihkaragoz/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/salihkaragoz/subscriptions","organizations_url":"https://api.github.com/users/salihkaragoz/orgs","repos_url":"https://api.github.com/users/salihkaragoz/repos","events_url":"https://api.github.com/users/salihkaragoz/events{/privacy}","received_events_url":"https://api.github.com/users/salihkaragoz/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-06-08T12:41:13Z","updated_at":"2018-06-22T13:03:59Z","closed_at":"2018-06-22T13:03:59Z","author_association":"NONE","body":"Great work, thank you for sharing code. \r\nI have a couple of questions related training set. \r\nIf I understand correctly;\r\nYou extracted images (frames of videos) according to 50 frames(but using of the one-tenth), then you cropped images with using the bounding box. My first question is that **how did you get these bounding boxes?** from Human3.6 annotations or some of the human detection model? and is there any resizing process on the boxes ?\r\n\r\nyour metafiles (.mat files) includes;\r\n\r\n['images_path',   ---> image path\r\n 'num_images',  ---> total images of that video\r\n 'Y2d               ',  ---> 2d coordinate of joints respect to 224x244 images.\r\n '__header__',\r\n '__globals__',\r\n 'bbox',            ---> bounding box coordinate (x0, y0,x1,y1) of cropped images respect to original image.\r\n 'Y3d_mono', ---> 3d room coordiante of joints but I am not sure\r\n '__version__']\r\n\r\nand also if you make some explanation related the Y3d_mono data it will be great. If I am correct it is the 3d locations respect to room coordinate. But where is the (0,0,0) coordinate? why some value is negative. \r\n\r\nSorry to bother you, Thanks in advance..."}}
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