{"action":"created","issue":{"url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/1359","repository_url":"https://api.github.com/repos/NVIDIA/DIGITS","labels_url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/1359/labels{/name}","comments_url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/1359/comments","events_url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/1359/events","html_url":"https://github.com/NVIDIA/DIGITS/issues/1359","id":197296077,"number":1359,"title":"Car-Pedestrian multi class object detection DetectNet mAP and inference","user":{"login":"eweill","id":6711990,"avatar_url":"https://avatars.githubusercontent.com/u/6711990?v=3","gravatar_id":"","url":"https://api.github.com/users/eweill","html_url":"https://github.com/eweill","followers_url":"https://api.github.com/users/eweill/followers","following_url":"https://api.github.com/users/eweill/following{/other_user}","gists_url":"https://api.github.com/users/eweill/gists{/gist_id}","starred_url":"https://api.github.com/users/eweill/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/eweill/subscriptions","organizations_url":"https://api.github.com/users/eweill/orgs","repos_url":"https://api.github.com/users/eweill/repos","events_url":"https://api.github.com/users/eweill/events{/privacy}","received_events_url":"https://api.github.com/users/eweill/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2016-12-23T00:50:28Z","updated_at":"2016-12-23T12:20:04Z","closed_at":null,"body":"I have been working on multi-class detection for cars and pedestrians using DetectNet, as mentioned in [MCOD](https://github.com/NVIDIA/DIGITS/pull/869#issuecomment-233909960).  I can successfully train a single-class DetectNet model for cars and pedestrians (separately); however I am unable to train the 2 class network correctly.  Note that when I try to train the pedestrian network on KITTI, I am achieving great classification but the mAP value does not reflect that (it hovers around 10 while I can get upwards of 55 for cars).\r\n\r\nWith that said, when I try to use the 2 class detect net with a dataset created from KITTI using dontcare,car,pedestrian it only seems to detect cars no pedestrians at all (i.e. the mAP for class 1 remains 0 for the entire training process).  I would like to perform inference on this, however with an mAP of 0, pedestrians aren't detected when using inference.\r\n\r\nCan anyone point me in the right direction when training the 2-class network? "},"comment":{"url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/comments/268982227","html_url":"https://github.com/NVIDIA/DIGITS/issues/1359#issuecomment-268982227","issue_url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/1359","id":268982227,"user":{"login":"varunvv","id":16333208,"avatar_url":"https://avatars.githubusercontent.com/u/16333208?v=3","gravatar_id":"","url":"https://api.github.com/users/varunvv","html_url":"https://github.com/varunvv","followers_url":"https://api.github.com/users/varunvv/followers","following_url":"https://api.github.com/users/varunvv/following{/other_user}","gists_url":"https://api.github.com/users/varunvv/gists{/gist_id}","starred_url":"https://api.github.com/users/varunvv/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/varunvv/subscriptions","organizations_url":"https://api.github.com/users/varunvv/orgs","repos_url":"https://api.github.com/users/varunvv/repos","events_url":"https://api.github.com/users/varunvv/events{/privacy}","received_events_url":"https://api.github.com/users/varunvv/received_events","type":"User","site_admin":false},"created_at":"2016-12-23T12:20:04Z","updated_at":"2016-12-23T12:20:04Z","body":"@eweill \r\n\r\nYou need to change the .prototxt file for detecting multi classes. Refer the links below\r\n\r\nhttps://github.com/NVIDIA/caffe/blob/caffe-0.15/examples/kitti/detectnet_network.prototxt\r\nhttps://github.com/NVIDIA/caffe/blob/caffe-0.15/examples/kitti/detectnet_network-2classes.prototxt"}}
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