{"action":"opened","issue":{"url":"https://api.github.com/repos/andy-yun/pytorch-0.4-yolov3/issues/39","repository_url":"https://api.github.com/repos/andy-yun/pytorch-0.4-yolov3","labels_url":"https://api.github.com/repos/andy-yun/pytorch-0.4-yolov3/issues/39/labels{/name}","comments_url":"https://api.github.com/repos/andy-yun/pytorch-0.4-yolov3/issues/39/comments","events_url":"https://api.github.com/repos/andy-yun/pytorch-0.4-yolov3/issues/39/events","html_url":"https://github.com/andy-yun/pytorch-0.4-yolov3/issues/39","id":392593639,"node_id":"MDU6SXNzdWUzOTI1OTM2Mzk=","number":39,"title":"About the predicted result","user":{"login":"LZZZZ29","id":38526431,"node_id":"MDQ6VXNlcjM4NTI2NDMx","avatar_url":"https://avatars1.githubusercontent.com/u/38526431?v=4","gravatar_id":"","url":"https://api.github.com/users/LZZZZ29","html_url":"https://github.com/LZZZZ29","followers_url":"https://api.github.com/users/LZZZZ29/followers","following_url":"https://api.github.com/users/LZZZZ29/following{/other_user}","gists_url":"https://api.github.com/users/LZZZZ29/gists{/gist_id}","starred_url":"https://api.github.com/users/LZZZZ29/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/LZZZZ29/subscriptions","organizations_url":"https://api.github.com/users/LZZZZ29/orgs","repos_url":"https://api.github.com/users/LZZZZ29/repos","events_url":"https://api.github.com/users/LZZZZ29/events{/privacy}","received_events_url":"https://api.github.com/users/LZZZZ29/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-12-19T13:06:52Z","updated_at":"2018-12-19T13:06:52Z","closed_at":null,"author_association":"NONE","body":"Hi, Andy. I have two questions about the output.\r\n\r\n1. I found that there is something wrong in the detected box. After using the function correct_yolo_boxes( ), the left, top of the box can be negative. \r\n\r\ne.g. -3.15759015083 26.1544475555 92.0868988037 106.778274536 \r\n\r\n2. The conf_threshold used in testing is 0.5 while it is set to 0.25 in training. I think they should be the same.\r\n\r\nAnother question is about non-maximum suppression in training. I didn't find it in the training procedure. \r\nDo you use nms in the training procedure?\r\n\r\nMany thanks."}}
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