{"action":"created","issue":{"url":"https://api.github.com/repos/WalterMa/gluon-faster-rcnn/issues/5","repository_url":"https://api.github.com/repos/WalterMa/gluon-faster-rcnn","labels_url":"https://api.github.com/repos/WalterMa/gluon-faster-rcnn/issues/5/labels{/name}","comments_url":"https://api.github.com/repos/WalterMa/gluon-faster-rcnn/issues/5/comments","events_url":"https://api.github.com/repos/WalterMa/gluon-faster-rcnn/issues/5/events","html_url":"https://github.com/WalterMa/gluon-faster-rcnn/issues/5","id":350394994,"node_id":"MDU6SXNzdWUzNTAzOTQ5OTQ=","number":5,"title":"Issue with demo_faster_rcnn.py script.","user":{"login":"Ram124","id":39698171,"node_id":"MDQ6VXNlcjM5Njk4MTcx","avatar_url":"https://avatars0.githubusercontent.com/u/39698171?v=4","gravatar_id":"","url":"https://api.github.com/users/Ram124","html_url":"https://github.com/Ram124","followers_url":"https://api.github.com/users/Ram124/followers","following_url":"https://api.github.com/users/Ram124/following{/other_user}","gists_url":"https://api.github.com/users/Ram124/gists{/gist_id}","starred_url":"https://api.github.com/users/Ram124/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Ram124/subscriptions","organizations_url":"https://api.github.com/users/Ram124/orgs","repos_url":"https://api.github.com/users/Ram124/repos","events_url":"https://api.github.com/users/Ram124/events{/privacy}","received_events_url":"https://api.github.com/users/Ram124/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":3,"created_at":"2018-08-14T11:51:40Z","updated_at":"2018-08-15T12:02:17Z","closed_at":null,"author_association":"NONE","body":"Hi, \r\nI have done training on my own dataset and i got 70% accuracy after 4 epochs.. \r\nI want to visualize the output.. so i tried with demo script.. i gave 1 input image and tried with the trained model. i changed the class names in demo script.  \r\nbut i got this error..   Could you please let me know whats the problem.. Thank You\r\n\r\nTraceback (most recent call last):\r\n  File \"demo_faster_rcnn.py\", line 65, in <module>\r\n    cls, scores, bboxes = net(data.as_in_context(ctx), im_info.as_in_context(ctx))\r\n  File \"/home/ubuntu/anaconda3/lib/python3.6/site-packages/mxnet/gluon/block.py\", line 413, in __call__\r\n    return self.forward(*args)\r\n  File \"/home/ubuntu/anaconda3/lib/python3.6/site-packages/mxnet/gluon/block.py\", line 629, in forward\r\n    return self.hybrid_forward(ndarray, x, *args, **params)\r\n  File \"/home/ubuntu/gluon-faster-rcnn/rcnn/rcnn.py\", line 69, in hybrid_forward\r\n    rois = self.proposal(rpn_cls_prob, rpn_bbox_pred, im_info)\r\n  File \"/home/ubuntu/anaconda3/lib/python3.6/site-packages/mxnet/gluon/block.py\", line 413, in __call__\r\n    return self.forward(*args)\r\n  File \"/home/ubuntu/anaconda3/lib/python3.6/site-packages/mxnet/gluon/block.py\", line 629, in forward\r\n    return self.hybrid_forward(ndarray, x, *args, **params)\r\n  File \"/home/ubuntu/gluon-faster-rcnn/rcnn/proposal.py\", line 32, in hybrid_forward\r\n    threshold=self.rpn_nms_threshold, rpn_min_size=self.rpn_min_size)\r\n  File \"<string>\", line 82, in MultiProposal\r\n  File \"/home/ubuntu/anaconda3/lib/python3.6/site-packages/mxnet/_ctypes/ndarray.py\", line 92, in _imperative_invoke\r\n    ctypes.byref(out_stypes)))\r\n  File \"/home/ubuntu/anaconda3/lib/python3.6/site-packages/mxnet/base.py\", line 149, in check_call\r\n    raise MXNetError(py_str(_LIB.MXGetLastError()))\r\nmxnet.base.MXNetError: Cannot find argument 'cls_prob', Possible Arguments:\r\n----------------\r\nrpn_pre_nms_top_n : int, optional, default='6000'\r\n    Number of top scoring boxes to keep after applying NMS to RPN proposals\r\nrpn_post_nms_top_n : int, optional, default='300'\r\n    Overlap threshold used for non-maximumsuppresion(suppress boxes with IoU >= this threshold\r\nthreshold : float, optional, default=0.7\r\n    NMS value, below which to suppress.\r\nrpn_min_size : int, optional, default='16'\r\n    Minimum height or width in proposal\r\nscales : tuple of <float>, optional, default=[4,8,16,32]\r\n    Used to generate anchor windows by enumerating scales\r\nratios : tuple of <float>, optional, default=[0.5,1,2]\r\n    Used to generate anchor windows by enumerating ratios\r\nfeature_stride : int, optional, default='16'\r\n    The size of the receptive field each unit in the convolution layer of the rpn,for example the product of all stride's prior to this layer.\r\noutput_score : boolean, optional, default=0\r\n    Add score to outputs\r\niou_loss : boolean, optional, default=0\r\n    Usage of IoU Loss\r\n, in operator _contrib_MultiProposal(name=\"\", feature_stride=\"16\", ratios=\"(0.5, 1, 2)\", rpn_min_size=\"16\", scales=\"(8, 16, 32)\", rpn_post_nms_top_n=\"300\", rpn_pre_nms_top_n=\"6000\", threshold=\"0.7\", cls_prob=\"\r\n[[[[9.2525011e-01 9.8686647e-01 9.9559492e-01 ... 9.6093690e-01\r\n    9.3473071e-01 8.3388972e-01]\r\n   [9.8144472e-01 9.9909139e-01 9.9984789e-01 ... 9.9409735e-01\r\n    9.8589975e-01 9.3193233e-01]\r\n   [9.8883343e-01 9.9964535e-01 9.9995410e-01 ... 9.9763453e-01\r\n    9.9354243e-01 9.5571983e-01]\r\n   ...\r\n   [9.8543328e-01 9.9948043e-01 9.9991584e-01 ... 9.9969471e-01\r\n    9.9917930e-01 9.8851913e-01]\r\n   [9.7469234e-01 9.9870670e-01 9.9970120e-01 ... 9.9901140e-01\r\n    9.9767345e-01 9.7834754e-01]\r\n   [9.0814865e-01 9.8365211e-01 9.9276966e-01 ... 9.8466349e-01\r\n    9.7399849e-01 9.0880662e-01]]\r\n\r\n  [[9.0745032e-01 9.8171026e-01 9.9309546e-01 ... 9.4973421e-01\r\n    9.1728598e-01 8.1418854e-01]\r\n   [9.7337264e-01 9.9846858e-01 9.9970394e-01 ... 9.9094427e-01\r\n    9.7995251e-01 9.1768110e-01]\r\n   [9.8243284e-01 9.9936765e-01 9.9990177e-01 ... 9.9625152e-01\r\n    9.9037081e-01 9.4557309e-01]\r\n   ...\r\n   [9.7682333e-01 9.9898654e-01 9.9980742e-01 ... 9.9938107e-01\r\n    9.9859077e-01 9.8415011e-01]\r\n   [9.6041822e-01 9.9727988e-01 9.9929476e-01 ... 9.9794215e-01\r\n    9.9601054e-01 9.7078675e-01]\r\n   [8.7193352e-01 9.7200722e-01 9.8639816e-01 ... 9.7515827e-01\r\n    9.6249181e-01 8.8967586e-01]]\r\n\r\n  [[5.2806801e-01 5.3886396e-01 5.5010569e-01 ... 5.2669793e-01\r\n    5.2231640e-01 5.0962281e-01]\r\n   [5.3768706e-01 5.5899465e-01 5.7622200e-01 ... 5.5065542e-01\r\n    5.4214233e-01 5.2825642e-01]\r\n   [5.4670048e-01 5.8282024e-01 6.0394657e-01 ... 5.6064773e-01\r\n    5.5870861e-01 5.4004127e-01]\r\n   ...\r\n   [5.3445053e-01 5.7814318e-01 6.0343522e-01 ... 5.9942263e-01\r\n    5.9564185e-01 5.6060779e-01]\r\n   [5.3276056e-01 5.7079929e-01 5.9411222e-01 ... 5.9032643e-01\r\n    5.8910215e-01 5.5843079e-01]\r\n   [5.2759832e-01 5.5251533e-01 5.7285386e-01 ... 5.6627262e-01\r\n    5.6415069e-01 5.4235542e-01]]\r\n\r\n  ...\r\n\r\n  [[1.6489255e-01 5.4860741e-02 2.7824294e-02 ... 1.1167015e-01\r\n    1.5454119e-01 2.7348977e-01]\r\n   [7.4070774e-02 1.0540956e-02 3.4242510e-03 ... 3.8886167e-02\r\n    6.8945184e-02 1.8131968e-01]\r\n   [6.2780201e-02 6.9735665e-03 1.9518270e-03 ... 2.3429820e-02\r\n    4.5364555e-02 1.4465846e-01]\r\n   ...\r\n   [8.8465296e-02 1.4774417e-02 5.4020169e-03 ... 1.1072693e-02\r\n    1.9699827e-02 8.5111000e-02]\r\n   [1.4203803e-01 3.7630506e-02 2.2168955e-02 ... 3.7781410e-02\r\n    5.5475168e-02 1.4689194e-01]\r\n   [2.8729475e-01 1.7887905e-01 1.5341425e-01 ... 1.8521468e-01\r\n    2.1700267e-01 3.0219343e-01]]\r\n\r\n  [[7.6535888e-02 1.3174757e-02 4.5662634e-03 ... 3.9024629e-02\r\n    6.6420421e-02 1.6296616e-01]\r\n   [1.8801216e-02 8.8067626e-04 1.5799509e-04 ... 5.9979130e-03\r\n    1.4321312e-02 6.7583486e-02]\r\n   [1.2135372e-02 3.7127602e-04 5.5430377e-05 ... 2.5837927e-03\r\n    6.8379878e-03 4.4826828e-02]\r\n   ...\r\n   [1.6011752e-02 5.7889975e-04 1.1127151e-04 ... 3.9832355e-04\r\n    9.8138128e-04 1.2958074e-02]\r\n   [2.6029671e-02 1.4883390e-03 3.9916934e-04 ... 1.2645581e-03\r\n    2.7250603e-03 2.4580965e-02]\r\n   [1.0069502e-01 1.9385004e-02 9.5264316e-03 ... 1.9384181e-02\r\n    3.1448375e-02 1.0509791e-01]]\r\n\r\n  [[4.3997696e-01 3.9228746e-01 3.6535779e-01 ... 4.2972672e-01\r\n    4.3877992e-01 4.6890491e-01]\r\n   [4.0322891e-01 3.3196816e-01 3.0024055e-01 ... 3.9013031e-01\r\n    4.0616569e-01 4.5436901e-01]\r\n   [4.0472379e-01 3.2188171e-01 2.8730047e-01 ... 3.8169590e-01\r\n    3.9514536e-01 4.5027012e-01]\r\n   ...\r\n   [4.1938949e-01 3.4382537e-01 3.1303972e-01 ... 3.3924583e-01\r\n    3.4913608e-01 4.1282722e-01]\r\n   [4.3390730e-01 3.7113073e-01 3.4658235e-01 ... 3.7191394e-01\r\n    3.8552991e-01 4.3190357e-01]\r\n   [4.6732298e-01 4.3559861e-01 4.2490643e-01 ... 4.4331262e-01\r\n    4.5451128e-01 4.7383672e-01]]]]\r\n<NDArray 1x18x37x37 @gpu(0)>\")\r\n"},"comment":{"url":"https://api.github.com/repos/WalterMa/gluon-faster-rcnn/issues/comments/413177256","html_url":"https://github.com/WalterMa/gluon-faster-rcnn/issues/5#issuecomment-413177256","issue_url":"https://api.github.com/repos/WalterMa/gluon-faster-rcnn/issues/5","id":413177256,"node_id":"MDEyOklzc3VlQ29tbWVudDQxMzE3NzI1Ng==","user":{"login":"Ram124","id":39698171,"node_id":"MDQ6VXNlcjM5Njk4MTcx","avatar_url":"https://avatars0.githubusercontent.com/u/39698171?v=4","gravatar_id":"","url":"https://api.github.com/users/Ram124","html_url":"https://github.com/Ram124","followers_url":"https://api.github.com/users/Ram124/followers","following_url":"https://api.github.com/users/Ram124/following{/other_user}","gists_url":"https://api.github.com/users/Ram124/gists{/gist_id}","starred_url":"https://api.github.com/users/Ram124/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Ram124/subscriptions","organizations_url":"https://api.github.com/users/Ram124/orgs","repos_url":"https://api.github.com/users/Ram124/repos","events_url":"https://api.github.com/users/Ram124/events{/privacy}","received_events_url":"https://api.github.com/users/Ram124/received_events","type":"User","site_admin":false},"created_at":"2018-08-15T12:02:17Z","updated_at":"2018-08-15T12:02:17Z","author_association":"NONE","body":"in ubuntu, \r\nsudo pip install --upgrade mxnet?? \r\nor other command?"}}
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