Open yyuan01 opened 4 years ago
I meet the same problem. In inference.py-->forward_single_image(), the res contains bool type, but the torch.stack seems not to support the bool input, so I change the type of res before the operation of stack, that is 'res = [o.int() for o in res]', it can work well.
Problem solved by updating pytorch to v1.3.0 with no code changes! The whole process of training and testing can be finished without problems after updating.
🐛 Bug
Traceback (most recent call last): File "webcam.py", line 83, in
main()
File "webcam.py", line 73, in main
composite = coco_demo.run_on_opencv_image(img)
File "/home/yuanyuan/maskrcnn-benchmark/demo/predictor.py", line 211, in run_on_opencv_image
predictions = self.compute_prediction(image)
File "/home/yuanyuan/maskrcnn-benchmark/demo/predictor.py", line 261, in compute_prediction
masks = self.masker([masks], [prediction])[0]
File "/home/yuanyuan/maskrcnn-benchmark/maskrcnn-benchmark/maskrcnn_benchmark/modeling/roi_heads/mask_head/inference.py", line 199, in call
result = self.forward_single_image(mask, box)
File "/home/yuanyuan/maskrcnn-benchmark/maskrcnn-benchmark/maskrcnn_benchmark/modeling/roi_heads/mask_head/inference.py", line 182, in forward_single_image
res = torch.stack(res, dim=0)[:, None]
RuntimeError: _th_cat is not implemented for type CPUBoolType
However after I delete the line masks = self.masker([masks], [prediction])[0] in predictor.py under demo, it works pretty well and I got the predicted results out.
To Reproduce
Steps to reproduce the behavior:
Expected behavior
Environment
Please copy and paste the output from the environment collection script from PyTorch (or fill out the checklist below manually).
You can get the script and run it with:
Collecting environment information... PyTorch version: 1.0.0.dev20190328 Is debug build: No CUDA used to build PyTorch: 10.0.130
OS: Ubuntu 18.04.2 LTS GCC version: (Ubuntu 7.4.0-1ubuntu1~18.04) 7.4.0 CMake version: version 3.10.2
Python version: 3.7 Is CUDA available: Yes CUDA runtime version: 10.0.130 GPU models and configuration: GPU: Tesla M40 24GB
Nvidia driver version: 418.67 cuDNN version: /usr/lib/x86_64-linux-gnu/libcudnn.so.7.6.0
Versions of relevant libraries: [pip3] numpy==1.17.2 [pip3] torch==1.2.0 [pip3] torchvision==0.4.0 [conda] blas 1.0 mkl
[conda] mkl 2019.4 243
[conda] mkl-service 2.3.0 py37he904b0f_0
[conda] mkl_fft 1.0.14 py37ha843d7b_0
[conda] mkl_random 1.1.0 py37hd6b4f25_0
[conda] pytorch 1.3.0 py3.7_cuda10.0.130_cudnn7.6.3_0 pytorch [conda] pytorch-nightly 1.0.0.dev20190328 py3.7_cuda10.0.130_cudnn7.4.2_0 pytorch [conda] torchvision 0.4.1 py37_cu100 pytorch
Additional context