{"action":"created","issue":{"url":"https://api.github.com/repos/KaiyangZhou/deep-person-reid/issues/24","repository_url":"https://api.github.com/repos/KaiyangZhou/deep-person-reid","labels_url":"https://api.github.com/repos/KaiyangZhou/deep-person-reid/issues/24/labels{/name}","comments_url":"https://api.github.com/repos/KaiyangZhou/deep-person-reid/issues/24/comments","events_url":"https://api.github.com/repos/KaiyangZhou/deep-person-reid/issues/24/events","html_url":"https://github.com/KaiyangZhou/deep-person-reid/issues/24","id":330250135,"node_id":"MDU6SXNzdWUzMzAyNTAxMzU=","number":24,"title":"Random image transformation probability","user":{"login":"ercanburak","id":17710818,"node_id":"MDQ6VXNlcjE3NzEwODE4","avatar_url":"https://avatars1.githubusercontent.com/u/17710818?v=4","gravatar_id":"","url":"https://api.github.com/users/ercanburak","html_url":"https://github.com/ercanburak","followers_url":"https://api.github.com/users/ercanburak/followers","following_url":"https://api.github.com/users/ercanburak/following{/other_user}","gists_url":"https://api.github.com/users/ercanburak/gists{/gist_id}","starred_url":"https://api.github.com/users/ercanburak/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/ercanburak/subscriptions","organizations_url":"https://api.github.com/users/ercanburak/orgs","repos_url":"https://api.github.com/users/ercanburak/repos","events_url":"https://api.github.com/users/ercanburak/events{/privacy}","received_events_url":"https://api.github.com/users/ercanburak/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":1,"created_at":"2018-06-07T12:28:22Z","updated_at":"2018-06-08T16:10:46Z","closed_at":null,"author_association":"NONE","body":"In [transforms.py](https://github.com/KaiyangZhou/deep-person-reid/blob/master/transforms.py), the probabilty variable p works the opposite way: Increasing p decreases the probability of performing the transformation. Line 31 can be changed to `if self.p < random.random():`\r\n\r\nAnd by the way, have you tried training a model with transformation probability other than p=0.5? In the triplet loss paper (In Defense of the Triplet Loss for Person Re-Identification), this probability seems like 1; it is stated that the transformation is done to all images. Can we expect increased scores with higher transformation probabilities?"},"comment":{"url":"https://api.github.com/repos/KaiyangZhou/deep-person-reid/issues/comments/395810124","html_url":"https://github.com/KaiyangZhou/deep-person-reid/issues/24#issuecomment-395810124","issue_url":"https://api.github.com/repos/KaiyangZhou/deep-person-reid/issues/24","id":395810124,"node_id":"MDEyOklzc3VlQ29tbWVudDM5NTgxMDEyNA==","user":{"login":"ercanburak","id":17710818,"node_id":"MDQ6VXNlcjE3NzEwODE4","avatar_url":"https://avatars1.githubusercontent.com/u/17710818?v=4","gravatar_id":"","url":"https://api.github.com/users/ercanburak","html_url":"https://github.com/ercanburak","followers_url":"https://api.github.com/users/ercanburak/followers","following_url":"https://api.github.com/users/ercanburak/following{/other_user}","gists_url":"https://api.github.com/users/ercanburak/gists{/gist_id}","starred_url":"https://api.github.com/users/ercanburak/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/ercanburak/subscriptions","organizations_url":"https://api.github.com/users/ercanburak/orgs","repos_url":"https://api.github.com/users/ercanburak/repos","events_url":"https://api.github.com/users/ercanburak/events{/privacy}","received_events_url":"https://api.github.com/users/ercanburak/received_events","type":"User","site_admin":false},"created_at":"2018-06-08T16:10:46Z","updated_at":"2018-06-08T16:10:46Z","author_association":"NONE","body":"I tried setting p=1 and training with ResNet50M, Market1501 and xent+htri loss, with keeping other settings at their defaults; and get an mAP of 75.1 and a rank-1 score of 90.6. Maybe optimizing other parameters may give slightly better scores. Anyway, thanks for the answer."}}
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