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Package Details: python-yolox 0.3.0-3
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Git Clone URL: | https://aur.archlinux.org/python-yolox.git (read-only, click to copy) |
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Package Base: | python-yolox |
Description: | YOLOX is an object detection method, an anchor-free version of YOLO, with a simpler design but better performance. |
Upstream URL: | https://github.com/Megvii-BaseDetection/YOLOX |
Keywords: | detection pytorch yolo |
Licenses: | MIT |
Submitter: | fanyujun |
Maintainer: | None |
Last Packager: | fanyujun |
Votes: | 0 |
Popularity: | 0.000000 |
First Submitted: | 2023-10-11 14:09 (UTC) |
Last Updated: | 2024-03-05 15:35 (UTC) |
Dependencies (16)
- python (python37AUR, python311AUR, python310AUR)
- python-loguru
- python-numpy (python-numpy-flameAUR, python-numpy-gitAUR, python-numpy1AUR, python-numpy-mkl-tbbAUR, python-numpy-mklAUR, python-numpy-mkl-binAUR)
- python-onnx
- python-opencv
- python-psutil
- python-pycocotoolsAUR (python-mmpycocotoolsAUR)
- python-pytorch (python-pytorch-mkl-gitAUR, python-pytorch-cuda-gitAUR, python-pytorch-mkl-cuda-gitAUR, python-pytorch-cxx11abiAUR, python-pytorch-cxx11abi-optAUR, python-pytorch-cxx11abi-cudaAUR, python-pytorch-cxx11abi-opt-cudaAUR, python-pytorch-cxx11abi-rocmAUR, python-pytorch-cxx11abi-opt-rocmAUR, python-pytorch-rocm-binAUR, python-pytorch-cuda, python-pytorch-opt, python-pytorch-opt-cuda, python-pytorch-opt-rocm, python-pytorch-rocm)
- python-tabulate (python-tabulate-gitAUR)
- python-thopAUR
- python-tqdm
- python-setuptools (make)
- python-ninjaAUR (optional)
- python-onnx (optional)
- python-onnxsimAUR (optional)
- tensorboard (optional)
Latest Comments
MarsSeed commented on 2024-03-05 19:04 (UTC)
Please rename this package to
python-yolox-git
and reupload with that name.Also please implement a
pkgver()
function in PKGBUILD.Relevant guidelines:
https://wiki.archlinux.org/title/VCS_package_guidelines#Guidelines
fanyujun commented on 2023-10-11 16:22 (UTC) (edited on 2023-10-11 16:36 (UTC) by fanyujun)
Please note:
The original setup method is
python3 setup.py develop
, which usesdevelop
. But this is not necessary and may cause issues when installing via AUR. I changed it to the more common wayinstall
. It works fine in my PC. Other than this setup method, the package is fully consistent with the latest released source codes.You may need to request issues in https://github.com/Megvii-BaseDetection/YOLOX.
Some issues I have encountered and solved:
exps/example/custom/yolox_s.py doesn't contains class named 'Exp'
.You can refer to discussions in this issue https://github.com/Megvii-BaseDetection/YOLOX/issues/1536.
.yolox.***
, it is suggested to modify it consistently toyolox.***
.