subprocess-exited-with-error when install nndetection

[liuxia0725]

Obtaining file:///D:/nnDetection Preparing metadata (setup.py) ... error error: subprocess-exited-with-error

× python setup.py egg_info did not run successfully. │ exit code: 1 ╰─> [8 lines of output] Traceback (most recent call last): File "", line 2, in File "", line 34, in File "D:\nnDetection\setup.py", line 7, in from torch.utils.cpp_extension import BuildExtension, CppExtension, CUDAExtension, CUDA_HOME File "E:\anaconda3\envs\new_env\lib\site-packages\torch\utils\cpp_extension.py", line 25, in from pkg_resources import packaging # type: ignore[attr-defined] ImportError: cannot import name 'packaging' from 'pkg_resources' (E:\anaconda3\envs\new_env\lib\site-packages\pkg_resources_init_.py) [end of output]

note: This error originates from a subprocess, and is likely not a problem with pip. error: metadata-generation-failed

× Encountered error while generating package metadata. ╰─> See above for output.

note: This is an issue with the package mentioned above, not pip. hint: See above for details.

how to solve this problem pytorch: 1.13.0, python 3.10; cuda 1.17

[mibaumgartner]

Dear @liuxia0725 ,

I haven't encountered this Issue before, could you try to run it in a linux based docker container? nnDetection does not officially support Windows and based on your file paths, it looks like you might be using a windows based operating system.

[parataaito]

Hi there!

Do you think that using WSL (Windows Subsystem for Linux) would work in that case?

EDIT: I managed to install docker and CUDA for docker in WSL using this procedure : http://collabnix.com/introducing-new-docker-cli-api-support-for-nvidia-gpus-under-docker-engine-19-03-0-beta-release/

I then installed nnDetection as decribed on the README.

I am currently running the nndet_example so it MAY have worked on Windows using WSL2!

I will follow up with my test if I manage to do the preprocessing and training

EDIT2: I was able to start the training of both the dummy dataset as well as a MSD Task dataset. So $\color{red}{\textsf{if you are stuck with Windows like I was, using WSL2 is indeed the way to go!}}$

[github-actions[bot]]

This issue is stale because it has been open for 30 days with no activity.

[github-actions[bot]]

This issue was closed because it has been inactive for 14 days since being marked as stale.