{"action":"opened","issue":{"url":"https://api.github.com/repos/Cartucho/mAP/issues/2","repository_url":"https://api.github.com/repos/Cartucho/mAP","labels_url":"https://api.github.com/repos/Cartucho/mAP/issues/2/labels{/name}","comments_url":"https://api.github.com/repos/Cartucho/mAP/issues/2/comments","events_url":"https://api.github.com/repos/Cartucho/mAP/issues/2/events","html_url":"https://github.com/Cartucho/mAP/issues/2","id":308222778,"number":2,"title":"Possibility to have class specific overlap threshold","user":{"login":"LucasVandroux","id":1956886,"avatar_url":"https://avatars3.githubusercontent.com/u/1956886?v=4","gravatar_id":"","url":"https://api.github.com/users/LucasVandroux","html_url":"https://github.com/LucasVandroux","followers_url":"https://api.github.com/users/LucasVandroux/followers","following_url":"https://api.github.com/users/LucasVandroux/following{/other_user}","gists_url":"https://api.github.com/users/LucasVandroux/gists{/gist_id}","starred_url":"https://api.github.com/users/LucasVandroux/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/LucasVandroux/subscriptions","organizations_url":"https://api.github.com/users/LucasVandroux/orgs","repos_url":"https://api.github.com/users/LucasVandroux/repos","events_url":"https://api.github.com/users/LucasVandroux/events{/privacy}","received_events_url":"https://api.github.com/users/LucasVandroux/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-03-24T02:38:55Z","updated_at":"2018-03-24T02:38:55Z","closed_at":null,"author_association":"NONE","body":"At first glance, your repo looks nice. You have lots of illustrations to explain the interpolated average precision which is really nice. However, is it possible to have a different threshold for different classes? For example, on the [KITTI benchmark](http://www.cvlibs.net/datasets/kitti/eval_object.php), the cars require an IoU over 70% to be considered as a correct detection while the pedestrians require 50%."}}
{"actor":{"display_login":"LucasVandroux"}}