Comments (4)
I have the same error too.
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from denseflow.
Hi, @RabiaCodes
I guess you should add the --gpus all
parameter when running denseflow on docker.
sudo docker run --gpus all
But I didn't test it. I failed to build it locally. And has anyone successfully built it and pushed it to Docker Hub? Thank you!
from denseflow.
In the Dockerfile, you have to set the CUDA and CUDNN versions such that it pulls a base container compatible with your graphics card, and you have to set the CUDA_GENERATION to be that of your card also. I have and RTX 3080 and so these were 11.4.0, 8, and Ampere respectively.
I was already using the --gpus all
and I think I had to install some nvidia runtime thing for docker as well before I found that to not solve this and updated these values. I do think the nvidia runtime is necessary also but can't say for sure.
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Related Issues (20)
- Encountered similar issue #33 HOT 1
- make -j error after open-cv with CUDA is installed HOT 2
- FPS in denseflow HOT 1
- Docker image not saving in h5 HOT 2
- Segmentation fault (core dumped) when few video frames HOT 7
- Unable to install opencv with cuda getting the error HOT 1
- opencv/modules/core/src/parallel.cpp:103:14: fatal error: tbb/tbb_stddef.h: No such file or directory
- how to add denseflow to PATH HOT 4
- Segmentation fault core dump HOT 1
- Timecode frame rate 23/1 not supported
- problem with command denseflow
- -o param(output dir) not working
- Is this repo still actively maintained? HOT 1
- denseflow多线程处理速度比单线程慢得多 HOT 2
- CMAKE ERROR HOT 2
- denseflow cannot extract frames of video HOT 1
- The last batch seems to be dropped when extracting flows. HOT 2
- make -j unrecognized ?
- cannot open video path stream!!!!!!
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