RuntimeError: Detectron2 is not compiled with GPU support!
hxue3 opened this issue · comments
I am trying to run the demo command and saw this error
[04/05 14:46:45 detectron2]: Arguments: Namespace(confidence_threshold=0.5, config_file='configs/GTR_TAO_DR2101.yaml', cpu=False, input=None, opts=['MODEL.WEIGHTS', 'models/GTR_TAO_DR2101.pth'], output='output/demo_yfcc.mp4', video_input='docs/yfcc_v_acef1cb6d38c2beab6e69e266e234f.mp4', webcam=None)
WARNING [04/05 14:46:45 d2.config.compat]: Config 'configs/GTR_TAO_DR2101.yaml' has no VERSION. Assuming it to be compatible with latest v2.
[04/05 14:47:30 fvcore.common.checkpoint]: [Checkpointer] Loading from models/GTR_TAO_DR2101.pth ...
WARNING [04/05 14:47:37 fvcore.common.checkpoint]: Some model parameters or buffers are not found in the checkpoint:
roi_heads.box_predictor.0.freq_weight
roi_heads.box_predictor.1.freq_weight
roi_heads.box_predictor.2.freq_weight
WARNING [04/05 14:47:37 fvcore.common.checkpoint]: The checkpoint state_dict contains keys that are not used by the model:
roi_heads.pos_emb.weight
Could not find encoder for codec id 27: Encoder not found
[ERROR:0] global /io/opencv/modules/videoio/src/cap.cpp (392) open VIDEOIO(CV_IMAGES): raised OpenCV exception:
OpenCV(4.1.2) /io/opencv/modules/videoio/src/cap_images.cpp:253: error: (-5:Bad argument) CAP_IMAGES: can't find starting number (in the name of file): /tmp/video_format_test3gfay7is/test_file.mkv in function 'icvExtractPattern'
Traceback (most recent call last):
File "demo.py", line 161, in
for vis_frame in demo.run_on_video(video):
File "/home/jupyter/GTR/gtr/predictor.py", line 146, in run_on_video
outputs = self.video_predictor(frames)
File "/opt/conda/envs/gtr/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "/home/jupyter/GTR/gtr/predictor.py", line 102, in call
predictions = self.model(inputs)
File "/opt/conda/envs/gtr/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/jupyter/GTR/gtr/modeling/meta_arch/gtr_rcnn.py", line 61, in forward
return self.sliding_inference(batched_inputs)
File "/home/jupyter/GTR/gtr/modeling/meta_arch/gtr_rcnn.py", line 81, in sliding_inference
instances_wo_id = self.inference(
File "/home/jupyter/GTR/gtr/modeling/meta_arch/custom_rcnn.py", line 107, in inference
features = self.backbone(images.tensor)
File "/opt/conda/envs/gtr/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/jupyter/detectron2/detectron2/modeling/backbone/fpn.py", line 126, in forward
bottom_up_features = self.bottom_up(x)
File "/opt/conda/envs/gtr/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/jupyter/GTR/third_party/CenterNet2/projects/CenterNet2/centernet/modeling/backbone/res2net.py", line 630, in forward
x = stage(x)
File "/opt/conda/envs/gtr/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/opt/conda/envs/gtr/lib/python3.8/site-packages/torch/nn/modules/container.py", line 119, in forward
input = module(input)
File "/opt/conda/envs/gtr/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/jupyter/GTR/third_party/CenterNet2/projects/CenterNet2/centernet/modeling/backbone/res2net.py", line 457, in forward
sp = self.convs[i](sp, offset, mask)
File "/opt/conda/envs/gtr/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/jupyter/detectron2/detectron2/layers/deform_conv.py", line 474, in forward
x = modulated_deform_conv(
File "/home/jupyter/detectron2/detectron2/layers/deform_conv.py", line 221, in forward
_C.modulated_deform_conv_forward(
RuntimeError: Detectron2 is not compiled with GPU support!
Hi,
Our model needs GPU for inference. Can check here and make sure your detectron2 is installed with GPU support?
Thanks. I have solved the problem. However, I noticed that when I tried a larger video file for the demo, it always says killed to stop the process. Is there a limit how big a video file can be handled byt GTR?
Hi, I have the same problem as you, how did you solve it?
Hi @hxue3 and @kele-git ,
The OOM issue for long videos is due to that we decode the entire compressed video into 3D tensors in preprocessing. There should be a (simple) way to only decode frames in a sliding window. I'll look into this hopefully in the following week(s), but feel free to play with it yourself.
Best,
Xingyi
Hi, I have the same problem as you, how did you solve it?
Did you manage to solve it?
Is the detected model combined with the tracked model? I didn't find the output of the test. I look forward to your answer？