{"action":"created","issue":{"url":"https://api.github.com/repos/thtrieu/darkflow/issues/356","repository_url":"https://api.github.com/repos/thtrieu/darkflow","labels_url":"https://api.github.com/repos/thtrieu/darkflow/issues/356/labels{/name}","comments_url":"https://api.github.com/repos/thtrieu/darkflow/issues/356/comments","events_url":"https://api.github.com/repos/thtrieu/darkflow/issues/356/events","html_url":"https://github.com/thtrieu/darkflow/issues/356","id":245660948,"number":356,"title":"Found a bug if there are multiple objects in the same cell during training","user":{"login":"zlmlaker","id":20418361,"avatar_url":"https://avatars3.githubusercontent.com/u/20418361?v=4","gravatar_id":"","url":"https://api.github.com/users/zlmlaker","html_url":"https://github.com/zlmlaker","followers_url":"https://api.github.com/users/zlmlaker/followers","following_url":"https://api.github.com/users/zlmlaker/following{/other_user}","gists_url":"https://api.github.com/users/zlmlaker/gists{/gist_id}","starred_url":"https://api.github.com/users/zlmlaker/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/zlmlaker/subscriptions","organizations_url":"https://api.github.com/users/zlmlaker/orgs","repos_url":"https://api.github.com/users/zlmlaker/repos","events_url":"https://api.github.com/users/zlmlaker/events{/privacy}","received_events_url":"https://api.github.com/users/zlmlaker/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2017-07-26T09:30:03Z","updated_at":"2017-08-02T00:56:34Z","closed_at":null,"body":"The _batch func in data.py seems to neglect some cases where there are more than one objects centered in the same cell. The produced label only takes the last object into consideration. So the network only cares about one image in the each cell during training.  It seems a bug to me because in darknet each gt-box is treated independently even if there are more than one object in a cell."},"comment":{"url":"https://api.github.com/repos/thtrieu/darkflow/issues/comments/319537862","html_url":"https://github.com/thtrieu/darkflow/issues/356#issuecomment-319537862","issue_url":"https://api.github.com/repos/thtrieu/darkflow/issues/356","id":319537862,"user":{"login":"simonxue","id":893253,"avatar_url":"https://avatars1.githubusercontent.com/u/893253?v=4","gravatar_id":"","url":"https://api.github.com/users/simonxue","html_url":"https://github.com/simonxue","followers_url":"https://api.github.com/users/simonxue/followers","following_url":"https://api.github.com/users/simonxue/following{/other_user}","gists_url":"https://api.github.com/users/simonxue/gists{/gist_id}","starred_url":"https://api.github.com/users/simonxue/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/simonxue/subscriptions","organizations_url":"https://api.github.com/users/simonxue/orgs","repos_url":"https://api.github.com/users/simonxue/repos","events_url":"https://api.github.com/users/simonxue/events{/privacy}","received_events_url":"https://api.github.com/users/simonxue/received_events","type":"User","site_admin":false},"created_at":"2017-08-02T00:56:34Z","updated_at":"2017-08-02T00:56:34Z","body":"I've read the code and agree with you. According to YOLO9000 paper, \"Multi-Scale Training\" might be able to mitigate this problem. Introducing some kind of randomness in the ground truth bbox selection might help too."}}
{"actor":{"display_login":"simonxue"}}