4.11.0.20250124
OpenCV python wheels built against CUDA 12.8, Nvidia Video Codec SDK 12.2 and cuDNN 9.7.0.
Suitable for all devices of compute capability >= 5.0 with binary compatible code for devices of compute capability 5.0-12.0.
Nvidia GPU Computing Toolkit v12.8 is required for import cv2
to work and cuDNN 9.7.0 for accelerated inference when using the dnn module.
Note Windows OS: This wheel relies on cuDNN being installed in the CUDA Toolkit directory. Therefore you can either download
-
the cuDNN Tarball (Version->Tarball) and extract its contents to your CUDA directory, or
-
the installer (Version->exe (local)) and the add the path to the bin folder inside the cuDNN installation directory to your PATH_TO_PYTHON_DIST/Lib/site-packages/cv2/config.py file. e.g.
import os
BINARIES_PATHS = [
os.path.join('D:/build/opencv/install', 'x64/vc17/bin'),
os.path.join(os.getenv('CUDA_PATH', 'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.8'), 'bin')
os.path.join('C:/Program Files/NVIDIA/CUDNN/v9.7/bin/12.8')
] + BINARIES_PATHS
Nvidia CMake configuration output
-- NVIDIA CUDA: YES (ver 12.8, CUFFT CUBLAS NVCUVID NVCUVENC)
-- NVIDIA GPU arch: 50 52 60 61 70 75 80 86 89 90 100 120
-- NVIDIA PTX archs: 120
--
-- cuDNN: YES (ver 9.7.0)
Build Summary
Windows Build commands
set "CMAKE_ARGS=-DWITH_CUDA=ON -DCUDA_ARCH_BIN=5.0;5.2;6.0;6.1;7.0;7.5;8.0;8.6;8.9;9.0;10.0;12.0 -DCUDA_ARCH_PTX=12.0"
set ENABLE_CONTRIB=1
set ENABLE_ROLLING=1
python.exe setup.py bdist_wheel --py-limited-api=cp37
Ubuntu 22.04 Build commands
export "CMAKE_ARGS=-DWITH_CUDA=ON -DCUDA_ARCH_BIN=5.0;5.2;6.0;6.1;7.0;7.5;8.0;8.6;8.9;9.0;10.0;12.0 -DCUDA_ARCH_PTX=12.0"
export ENABLE_CONTRIB=1
export ENABLE_ROLLING=1
python setup.py bdist_wheel --py-limited-api=cp37