-
Notifications
You must be signed in to change notification settings - Fork 2
Required python packages
All required packages are automatically installed. However, in some cases, the correct package version may not be installed, causing problems when running.
-
mmcv == 2.1.0(install usingmim install mmcv) mmengine == 0.8.5-
mmyolo == 0.6.0(install usingpip install mmyolo)
-
mmyolo 0.6.0 may not work with
mmcv==2.1.1but you can fix this issue by patching manually. fix version restriction atvenv/Lib/site-packages/mmyolo/__init__.py(fixmmcv_maximum_version = '2.1.0'tommcv_maximum_version = '2.1.1'works just fine. -
mmengine
0.9.1will not work under windows. but you can use mmengine0.9.1+ patchedbitsnbytesat https://github.com/wkpark/bitsandbytes/actions/runs/6887358987 (login github and scroll down you will find a downloadable artifacts)
- open
cmdprompt or use terminal shell. - change to the
sdwebuidir and enablevenv. (on Windows for example,cd stable-diffusion-webuiandvenv\scripts\activate) - install
mmcv==2.1.0ormmcv=2.0.0usingmim(to usemmcv==2.1.0you have to patchmmyolo/__init__.pymanually.)-
mim install mmcv==2.1.0,
-
in this case, mim install mmcv or mim install mmdet will try to compile it from source but failed.
- you need to prepare CUDA 12.1.x on your system.
pip install mmdetpip install mmcv==2.1.0 -f https://download.openmmlab.com/mmcv/dist/cu121/torch2.1/index.htmlpip install mmyolo
in this case, mim install mmdet will automatically try to compile mmcv from source tarball. we need MSVC compiler.
- check torch version and your CUDA version: for example, if you use torch-2.2.0+cu121, you have to match CUDA 12.1.x on your system.
- install visual studio 2022
- open
x64 native command prompt -
mim install mmcvwill automatically compile mmcv for you.
Even if you can't use mmdet models due to issues like mmcv version issue, you can still use mediapipe_* models or ultralytics yolov8 models.