{"action":"created","issue":{"url":"https://api.github.com/repos/precedenceguo/mx-rcnn/issues/19","repository_url":"https://api.github.com/repos/precedenceguo/mx-rcnn","labels_url":"https://api.github.com/repos/precedenceguo/mx-rcnn/issues/19/labels{/name}","comments_url":"https://api.github.com/repos/precedenceguo/mx-rcnn/issues/19/comments","events_url":"https://api.github.com/repos/precedenceguo/mx-rcnn/issues/19/events","html_url":"https://github.com/precedenceguo/mx-rcnn/issues/19","id":170824862,"number":19,"title":"a question about rcnn training with batch_size > 1","user":{"login":"tornadomeet","id":5860892,"avatar_url":"https://avatars.githubusercontent.com/u/5860892?v=3","gravatar_id":"","url":"https://api.github.com/users/tornadomeet","html_url":"https://github.com/tornadomeet","followers_url":"https://api.github.com/users/tornadomeet/followers","following_url":"https://api.github.com/users/tornadomeet/following{/other_user}","gists_url":"https://api.github.com/users/tornadomeet/gists{/gist_id}","starred_url":"https://api.github.com/users/tornadomeet/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/tornadomeet/subscriptions","organizations_url":"https://api.github.com/users/tornadomeet/orgs","repos_url":"https://api.github.com/users/tornadomeet/repos","events_url":"https://api.github.com/users/tornadomeet/events{/privacy}","received_events_url":"https://api.github.com/users/tornadomeet/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":1,"created_at":"2016-08-12T08:42:40Z","updated_at":"2016-08-12T09:04:41Z","closed_at":null,"body":"hello, @precedenceguo \r\nmx-rcnn is a great work!\r\n\r\ni just found mx-rcnn support training with batch_size > 1 during train_rcnn() training, it use max size(of the same mini-batch) of each dim to solve different size of each instance, if the dim is shorter than the max dim, then it will pad 0 in the end: \r\n```python\r\ntensor_list[ind] = np.lib.pad(tensor, pad_shape, 'constant', constant_values=pad)\r\n```\r\ndoes this will influence the training accuracy? during training, this may changed the input data of roi-pooling, if pad size is too large, then the last area of roi-pooling's output will be meaningless. and during testing, we need no more to pad before roi-pooling, so the behavior maybe changed."},"comment":{"url":"https://api.github.com/repos/precedenceguo/mx-rcnn/issues/comments/239397260","html_url":"https://github.com/precedenceguo/mx-rcnn/issues/19#issuecomment-239397260","issue_url":"https://api.github.com/repos/precedenceguo/mx-rcnn/issues/19","id":239397260,"user":{"login":"precedenceguo","id":13162287,"avatar_url":"https://avatars.githubusercontent.com/u/13162287?v=3","gravatar_id":"","url":"https://api.github.com/users/precedenceguo","html_url":"https://github.com/precedenceguo","followers_url":"https://api.github.com/users/precedenceguo/followers","following_url":"https://api.github.com/users/precedenceguo/following{/other_user}","gists_url":"https://api.github.com/users/precedenceguo/gists{/gist_id}","starred_url":"https://api.github.com/users/precedenceguo/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/precedenceguo/subscriptions","organizations_url":"https://api.github.com/users/precedenceguo/orgs","repos_url":"https://api.github.com/users/precedenceguo/repos","events_url":"https://api.github.com/users/precedenceguo/events{/privacy}","received_events_url":"https://api.github.com/users/precedenceguo/received_events","type":"User","site_admin":false},"created_at":"2016-08-12T09:04:41Z","updated_at":"2016-08-12T09:04:41Z","body":"The padded zeros are backgrounds which will be neglected because no roi coordinates covering padded regions are supplied to roi-pooling. In other words, they will never be pooled from feature maps."}}
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