{"action":"opened","issue":{"url":"https://api.github.com/repos/facebookresearch/Detectron/issues/330","repository_url":"https://api.github.com/repos/facebookresearch/Detectron","labels_url":"https://api.github.com/repos/facebookresearch/Detectron/issues/330/labels{/name}","comments_url":"https://api.github.com/repos/facebookresearch/Detectron/issues/330/comments","events_url":"https://api.github.com/repos/facebookresearch/Detectron/issues/330/events","html_url":"https://github.com/facebookresearch/Detectron/issues/330","id":310225596,"number":330,"title":"How to use not end-to-end model in Detectron?","user":{"login":"Markovcom","id":26458922,"avatar_url":"https://avatars0.githubusercontent.com/u/26458922?v=4","gravatar_id":"","url":"https://api.github.com/users/Markovcom","html_url":"https://github.com/Markovcom","followers_url":"https://api.github.com/users/Markovcom/followers","following_url":"https://api.github.com/users/Markovcom/following{/other_user}","gists_url":"https://api.github.com/users/Markovcom/gists{/gist_id}","starred_url":"https://api.github.com/users/Markovcom/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Markovcom/subscriptions","organizations_url":"https://api.github.com/users/Markovcom/orgs","repos_url":"https://api.github.com/users/Markovcom/repos","events_url":"https://api.github.com/users/Markovcom/events{/privacy}","received_events_url":"https://api.github.com/users/Markovcom/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-03-31T09:01:56Z","updated_at":"2018-03-31T09:01:56Z","closed_at":null,"author_association":"NONE","body":"zhoulinmao@vismod-server-02:/home/code/zhoulinmao/FAIR/detectron$ CUDA_VISIBLE_DEVICES=3 python2 tools/infer_simple.py \\\r\n>     --cfg configs/12_2017_baselines/rpn_person_only_X-101-32x8d-FPN_1x.yaml \\\r\n>     --output-dir demo/output-test \\\r\n>     --image-ext jpg \\\r\n>     --wts models/rpn_person_only_X-101-32x8d-FPN_1x/model_final.pkl \\\r\n>     demo/data/frame-test/\r\n\r\nI use the not end-to-end model in detectron in this way,i meet this problem?\r\n\r\nFound Detectron ops lib: /home/zhoulinmao/caffe2/build/lib/libcaffe2_detectron_ops_gpu.so\r\nE0331 16:39:00.946282 31251 init_intrinsics_check.cc:59] CPU feature avx is present on your machine, but the Caffe2 binary is not compiled with it. It means you may not get the full speed of your CPU.\r\nE0331 16:39:00.946311 31251 init_intrinsics_check.cc:59] CPU feature avx2 is present on your machine, but the Caffe2 binary is not compiled with it. It means you may not get the full speed of your CPU.\r\nE0331 16:39:00.946317 31251 init_intrinsics_check.cc:59] CPU feature fma is present on your machine, but the Caffe2 binary is not compiled with it. It means you may not get the full speed of your CPU.\r\nWARNING cnn.py:  40: [====DEPRECATE WARNING====]: you are creating an object from CNNModelHelper class which will be deprecated soon. Please use ModelHelper object with brew module. For more information, please refer to caffe2.ai and python/brew.py, python/brew_test.py for more information.\r\nINFO net.py:  57: Loading weights from: models/rpn_person_only_X-101-32x8d-FPN_1x/model_final.pkl\r\nI0331 16:39:07.971232 31251 net_dag_utils.cc:118] Operator graph pruning prior to chain compute took: 0.000165332 secs\r\nI0331 16:39:07.971550 31251 net_dag.cc:61] Number of parallel execution chains 52 Number of operators = 388\r\nI0331 16:39:07.997779 31251 net_dag_utils.cc:118] Operator graph pruning prior to chain compute took: 0.000178957 secs\r\nI0331 16:39:07.998018 31251 net_dag.cc:61] Number of parallel execution chains 30 Number of operators = 358\r\nINFO infer_simple.py: 112: Processing demo/data/frame-test/frame778.jpg -> demo/output-test/frame778.jpg.pdf\r\nTraceback (most recent call last):\r\n  File \"tools/infer_simple.py\", line 148, in <module>\r\n    main(args)\r\n  File \"tools/infer_simple.py\", line 118, in main\r\n    model, im, None, timers=timers\r\n  File \"/home/code/zhoulinmao/FAIR/detectron/lib/core/test.py\", line 66, in im_detect_all\r\n    model, im, cfg.TEST.SCALE, cfg.TEST.MAX_SIZE, boxes=box_proposals\r\n  File \"/home/code/zhoulinmao/FAIR/detectron/lib/core/test.py\", line 145, in im_detect_bbox\r\n    hashes = np.round(inputs['rois'] * cfg.DEDUP_BOXES).dot(v)\r\nKeyError: u'rois'\r\n"}}
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