{"action":"opened","issue":{"url":"https://api.github.com/repos/una-dinosauria/3d-pose-baseline/issues/60","repository_url":"https://api.github.com/repos/una-dinosauria/3d-pose-baseline","labels_url":"https://api.github.com/repos/una-dinosauria/3d-pose-baseline/issues/60/labels{/name}","comments_url":"https://api.github.com/repos/una-dinosauria/3d-pose-baseline/issues/60/comments","events_url":"https://api.github.com/repos/una-dinosauria/3d-pose-baseline/issues/60/events","html_url":"https://github.com/una-dinosauria/3d-pose-baseline/issues/60","id":323893848,"number":60,"title":"Replicating GT/SH in Table 1","user":{"login":"matteorr","id":3580181,"avatar_url":"https://avatars3.githubusercontent.com/u/3580181?v=4","gravatar_id":"","url":"https://api.github.com/users/matteorr","html_url":"https://github.com/matteorr","followers_url":"https://api.github.com/users/matteorr/followers","following_url":"https://api.github.com/users/matteorr/following{/other_user}","gists_url":"https://api.github.com/users/matteorr/gists{/gist_id}","starred_url":"https://api.github.com/users/matteorr/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/matteorr/subscriptions","organizations_url":"https://api.github.com/users/matteorr/orgs","repos_url":"https://api.github.com/users/matteorr/repos","events_url":"https://api.github.com/users/matteorr/events{/privacy}","received_events_url":"https://api.github.com/users/matteorr/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-05-17T06:54:34Z","updated_at":"2018-05-17T06:54:34Z","closed_at":null,"author_association":"NONE","body":"I have a question about the experiment GT/SH described in Table 1.\r\nIf I understand correctly this is the setup:\r\n- Train input is 16 (i.e. 17 - neck) ground truth 2D keypoints using all the videos from subjects 1,5,6,7,8.\r\n- Test input is 16 stacked hourglass 2D keypoints using all the videos from subjects 9 and all the videos except Directions from subject 11.\r\n- Output for both train and test is 17 3D keypoints.\r\n- Protocol #2 is used, which corresponds to using all frames, all cameras, averaging over the actions, and using Procrustes alignment.\r\n\r\nIn order to replicate the above setup I changed the following [lines in your code](https://github.com/una-dinosauria/3d-pose-baseline/blob/master/src/predict_3dpose.py#L157-L161) from:\r\n\r\n```\r\n# Read stacked hourglass 2D predictions if use_sh, otherwise use groundtruth 2D projections\r\nif FLAGS.use_sh:\r\n  train_set_2d, test_set_2d, data_mean_2d, data_std_2d, dim_to_ignore_2d, dim_to_use_2d = data_utils.read_2d_predictions(actions, FLAGS.data_dir)\r\nelse:\r\n  train_set_2d, test_set_2d, data_mean_2d, data_std_2d, dim_to_ignore_2d, dim_to_use_2d = data_utils.create_2d_data( actions, FLAGS.data_dir, rcams )\r\n```\r\n\r\nto\r\n\r\n```\r\n# Use GT for train and SH for test\r\ntrain_set_2d, _, data_mean_2d, data_std_2d, dim_to_ignore_2d, dim_to_use_2d = data_utils.create_2d_data( actions, FLAGS.data_dir, rcams )\r\n_, test_set_2d, _, _, _, _  = data_utils.read_2d_predictions(actions, FLAGS.data_dir)\r\n```\r\nso I can train on GT and test on SH (i.e. GT/SH) instead of SH/SH or GT/GT.\r\n\r\nHowever, I'm having hard time getting 60.52, since at the first epoch the error is 63.95 and it grows instead of decreasing, i.e. at epoch 5 it is 66.58.\r\n\r\nI used the following command to train:\r\n`python src/predict_3dpose.py --camera_frame --residual --batch_norm --dropout 0.5 --max_norm --evaluateActionWise --use_sh --epochs 100`\r\n\r\nThanks a lot for any help on this matter!\r\n"}}
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