{"action":"opened","issue":{"url":"https://api.github.com/repos/open-mmlab/mmdetection/issues/1442","repository_url":"https://api.github.com/repos/open-mmlab/mmdetection","labels_url":"https://api.github.com/repos/open-mmlab/mmdetection/issues/1442/labels{/name}","comments_url":"https://api.github.com/repos/open-mmlab/mmdetection/issues/1442/comments","events_url":"https://api.github.com/repos/open-mmlab/mmdetection/issues/1442/events","html_url":"https://github.com/open-mmlab/mmdetection/issues/1442","id":497418368,"node_id":"MDU6SXNzdWU0OTc0MTgzNjg=","number":1442,"title":"bounded iou loss is  time-consuming","user":{"login":"scut-salmon","id":20534039,"node_id":"MDQ6VXNlcjIwNTM0MDM5","avatar_url":"https://avatars3.githubusercontent.com/u/20534039?v=4","gravatar_id":"","url":"https://api.github.com/users/scut-salmon","html_url":"https://github.com/scut-salmon","followers_url":"https://api.github.com/users/scut-salmon/followers","following_url":"https://api.github.com/users/scut-salmon/following{/other_user}","gists_url":"https://api.github.com/users/scut-salmon/gists{/gist_id}","starred_url":"https://api.github.com/users/scut-salmon/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/scut-salmon/subscriptions","organizations_url":"https://api.github.com/users/scut-salmon/orgs","repos_url":"https://api.github.com/users/scut-salmon/repos","events_url":"https://api.github.com/users/scut-salmon/events{/privacy}","received_events_url":"https://api.github.com/users/scut-salmon/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2019-09-24T02:24:47Z","updated_at":"2019-09-24T02:24:47Z","closed_at":null,"author_association":"NONE","body":"Hi, I found that when I change the smooth-L1 loss to bounded iou loss, the code become quite time-consuming and the loss is not stable, which may occur to large value, the same situation as iou loss.\r\n\r\nDid anyone meet the same question?\r\n\r\nThanks\r\nZhang"}}
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