ubuntu 编译安装支持CUDA的OpenCV
ubuntu 编译安装opencv 支持cuda
cuda和cudnn的安装相对简单这里就不过多解释。
一、安装opencv依赖包
sudo apt-get update
sudo apt-get upgrade
sudo apt install cmake pkg-config unzip yasm git checkinstall libjpeg-dev libpng-dev libtiff-dev libavcodec-dev libavformat-dev libswscale-dev libavresample-dev libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev libxvidcore-dev x264 libx264-dev libfaac-dev libmp3lame-dev libtheora-dev libfaac-dev libmp3lame-dev libvorbis-dev libopencore-amrnb-dev libopencore-amrwb-dev
sudo apt-get install libdc1394-22 libdc1394-22-dev libxine2-dev libv4l-dev v4l-utils
cd /usr/include/linux
sudo ln -s -f ../libv4l1-videodev.h videodev.h
cd ~
sudo apt-get install libgtk-3-dev libtbb-dev libatlas-base-dev gfortran
二、下载opencv和opencv_contrib并解压
cd ~/Downloads
wget -O opencv.zip https://github.com/opencv/opencv/archive/refs/tags/4.5.2.zip
wget -O opencv_contrib.zip https://github.com/opencv/opencv_contrib/archive/refs/tags/4.5.2.zip
unzip opencv.zip
unzip opencv_contrib.zip
三、开始编译
cd opencv-4.5.5
mkdir build
cd build
一定要在root中进行
cmake -D CMAKE_BUILD_TYPE=RELEASE \
-D CMAKE_INSTALL_PREFIX=/usr/local \
-D CMAKE_C_COMPILER=/usr/bin/gcc-9 \
-D INSTALL_PYTHON_EXAMPLES=ON \
-D INSTALL_C_EXAMPLES=ON \
-D OPENCV_ENABLE_NONFREE=ON \
-D BUILD_opencv_python3=ON \
-D WITH_CUDA=ON \
-D WITH_CUDNN=ON \
-D WITH_TBB=ON \
-D OPENCV_DNN_CUDA=ON \
-D ENABLE_FAST_MATH=1 \
-D CUDA_FAST_MATH=1 \
-D CUDA_ARCH_BIN=8.6 \
-D WITH_CUBLAS=1 \
-D OPENCV_GENERATE_PKGCONFIG=ON \
-D OPENCV_EXTRA_MODULES_PATH=/home/hb/Downloads/opencv-4.5.5/opencv_contrib-4.5.5/modules \
-D PYTHON3_EXECUTABLE=/home/hb/anaconda3/bin/python3.7m \
-D PYTHON3_INCLUDE_DIR=/home/hb/anaconda3/include/python3.7m \
-D PYTHON3_LIBRARY=/home/hb/anaconda3/lib/libpython3.7m.so \
-D PYTHON3_NUMPY_INCLUDE_DIRS=/home/hb/anaconda3/lib/python3.7/site-packages/numpy/core/include \
-D PYTHON3_PACKAGES_PATH=/home/hb/anaconda3/lib/python3.7/site-packages \
-D PYTHON_DEFAULT_EXECUTABLE=/home/hb/anaconda3/bin/python3.7m \
-D CUDNN_LIBRARY=/usr/local/cuda/lib64/libcudnn.so.8.3.3 \
-D CUDNN_INCLUDE_DIR=/usr/local/cuda/include \
-D CUDA_CUDA_LIBRARY=/usr/local/cuda/lib64/stubs/libcuda.so \
-D OPENCV_PYTHON3_INSTALL_PATH=/home/hb/anaconda3/lib/python3.7/site-packages \
-D WITH_WEBP=OFF \
-D WITH_OPENCL=OFF \
-D ETHASHLCL=OFF \
-D ENABLE_CXX11=ON \
-D BUILD_EXAMPLES=OFF \
-D OPENCV_ENABLE_NONFREE=ON \
-D WITH_OPENGL=ON \
-D WITH_GSTREAMER=ON \
-D WITH_V4L=ON \
-D WITH_QT=OFF \
-D BUILD_opencv_python3=ON \
-D BUILD_opencv_python2=OFF \
-D HAVE_opencv_python3=ON ..
！！！！！！
这里需要将这几个路径改成你自己的：
-D OPENCV_EXTRA_MODULES_PATH=/home/hb/Downloads/opencv-4.5.5/opencv_contrib-4.5.5/modules \
-D PYTHON3_EXECUTABLE=/home/hb/anaconda3/bin/python3.7m \
-D PYTHON3_INCLUDE_DIR=/home/hb/anaconda3/include/python3.7m \
-D PYTHON3_LIBRARY=/home/hb/anaconda3/lib/libpython3.7m.so \
-D PYTHON3_NUMPY_INCLUDE_DIRS=/home/hb/anaconda3/lib/python3.7/site-packages/numpy/core/include \
-D PYTHON3_PACKAGES_PATH=/home/hb/anaconda3/lib/python3.7/site-packages \
-D PYTHON_DEFAULT_EXECUTABLE=/home/hb/anaconda3/bin/python3.7m \
-D CUDNN_LIBRARY=/usr/local/cuda/lib64/libcudnn.so.8.3.3 \
-D CUDNN_INCLUDE_DIR=/usr/local/cuda/include \
-D CUDA_CUDA_LIBRARY=/usr/local/cuda/lib64/stubs/libcuda.so \
-D OPENCV_PYTHON3_INSTALL_PATH=/home/hb/anaconda3/lib/python3.7/site-packages \
然后：
nproc # 查看核数
make -jx #x是核数，加速编译
sudo make install
打把游戏，睡个午觉。然后不出意外就可以编译成功。
如果出现错误即使评论，大部分坑我已经踩过！
然后执行
sudo /bin/bash -c 'echo "/usr/local/lib" >> /etc/ld.so.conf.d/opencv.conf'
sudo ldconfig
四、检查是否安装成功
检查opencv是否安装成功：
pkg-config --modversion opencv
pkg-config --libs opencv4
在终端上启动 python 并执行以下操作：
import cv2
print(cv2.getBuildInformation())
打印信息如下：
General configuration for OpenCV 4.5.2 =====================================
Version control: unknown
Extra modules:
Location (extra): /home/hb/Downloads/opencv-4.5.2/opencv_contrib-4.5.2/modules
Version control (extra): unknown
Platform:
Timestamp: 2022-04-12T02:48:52Z
Host: Linux 5.14.0-1033-oem x86_64
CMake: 3.16.3
CMake generator: Unix Makefiles
CMake build tool: /usr/bin/make
Configuration: RELEASE
CPU/HW features:
Baseline: SSE SSE2 SSE3
requested: SSE3
Dispatched code generation: SSE4_1 SSE4_2 FP16 AVX AVX2 AVX512_SKX
requested: SSE4_1 SSE4_2 AVX FP16 AVX2 AVX512_SKX
SSE4_1 (17 files): + SSSE3 SSE4_1
SSE4_2 (2 files): + SSSE3 SSE4_1 POPCNT SSE4_2
FP16 (1 files): + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 AVX
AVX (5 files): + SSSE3 SSE4_1 POPCNT SSE4_2 AVX
AVX2 (31 files): + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 FMA3 AVX AVX2
AVX512_SKX (7 files): + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 FMA3 AVX AVX2 AVX_512F AVX512_COMMON AVX512_SKX
C/C++:
Built as dynamic libs?: YES
C++ standard: 11
C++ Compiler: /usr/bin/c++ (ver 9.4.0)
C++ flags (Release): -fsigned-char -ffast-math -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wundef -Winit-self -Wpointer-arith -Wshadow -Wsign-promo -Wuninitialized -Wsuggest-override -Wno-delete-non-virtual-dtor -Wno-comment -Wimplicit-fallthrough=3 -Wno-strict-overflow -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -msse -msse2 -msse3 -fvisibility=hidden -fvisibility-inlines-hidden -O3 -DNDEBUG -DNDEBUG
C++ flags (Debug): -fsigned-char -ffast-math -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wundef -Winit-self -Wpointer-arith -Wshadow -Wsign-promo -Wuninitialized -Wsuggest-override -Wno-delete-non-virtual-dtor -Wno-comment -Wimplicit-fallthrough=3 -Wno-strict-overflow -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -msse -msse2 -msse3 -fvisibility=hidden -fvisibility-inlines-hidden -g -O0 -DDEBUG -D_DEBUG
C Compiler: /usr/bin/gcc-9
C flags (Release): -fsigned-char -ffast-math -W -Wall -Werror=return-type -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wmissing-prototypes -Wstrict-prototypes -Wundef -Winit-self -Wpointer-arith -Wshadow -Wuninitialized -Wno-comment -Wimplicit-fallthrough=3 -Wno-strict-overflow -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -msse -msse2 -msse3 -fvisibility=hidden -O3 -DNDEBUG -DNDEBUG
C flags (Debug): -fsigned-char -ffast-math -W -Wall -Werror=return-type -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wmissing-prototypes -Wstrict-prototypes -Wundef -Winit-self -Wpointer-arith -Wshadow -Wuninitialized -Wno-comment -Wimplicit-fallthrough=3 -Wno-strict-overflow -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -msse -msse2 -msse3 -fvisibility=hidden -g -O0 -DDEBUG -D_DEBUG
Linker flags (Release): -Wl,--exclude-libs,libippicv.a -Wl,--exclude-libs,libippiw.a -Wl,--gc-sections -Wl,--as-needed
Linker flags (Debug): -Wl,--exclude-libs,libippicv.a -Wl,--exclude-libs,libippiw.a -Wl,--gc-sections -Wl,--as-needed
ccache: NO
Precompiled headers: NO
Extra dependencies: m pthread cudart_static dl rt nppc nppial nppicc nppidei nppif nppig nppim nppist nppisu nppitc npps cublas cudnn cufft -L/usr/local/cuda/lib64 -L/usr/lib/x86_64-linux-gnu
3rdparty dependencies:
OpenCV modules:
To be built: alphamat aruco bgsegm bioinspired calib3d ccalib core cudaarithm cudabgsegm cudacodec cudafeatures2d cudafilters cudaimgproc cudalegacy cudaobjdetect cudaoptflow cudastereo cudawarping cudev datasets dnn dnn_objdetect dnn_superres dpm face features2d flann freetype fuzzy gapi hdf hfs highgui img_hash imgcodecs imgproc intensity_transform java line_descriptor mcc ml objdetect optflow phase_unwrapping photo plot python3 quality rapid reg rgbd saliency sfm shape stereo stitching structured_light superres surface_matching text tracking ts video videoio videostab wechat_qrcode xfeatures2d ximgproc xobjdetect xphoto
Disabled: world
Disabled by dependency: -
Unavailable: cnn_3dobj cvv julia matlab ovis python2 viz
Applications: tests perf_tests apps
Documentation: NO
Non-free algorithms: YES
GUI:
GTK+: YES (ver 2.24.32)
GThread : YES (ver 2.64.6)
GtkGlExt: NO
OpenGL support: NO
VTK support: NO
Media I/O:
ZLib: /usr/lib/x86_64-linux-gnu/libz.so (ver 1.2.11)
JPEG: /usr/lib/x86_64-linux-gnu/libjpeg.so (ver 80)
PNG: /usr/lib/x86_64-linux-gnu/libpng.so (ver 1.6.37)
TIFF: /usr/lib/x86_64-linux-gnu/libtiff.so (ver 42 / 4.1.0)
JPEG 2000: build (ver 2.4.0)
OpenEXR: /usr/lib/x86_64-linux-gnu/libImath.so /usr/lib/x86_64-linux-gnu/libIlmImf.so /usr/lib/x86_64-linux-gnu/libIex.so /usr/lib/x86_64-linux-gnu/libHalf.so /usr/lib/x86_64-linux-gnu/libIlmThread.so (ver 2_3)
HDR: YES
SUNRASTER: YES
PXM: YES
PFM: YES
Video I/O:
DC1394: YES (2.2.5)
FFMPEG: YES
avcodec: YES (58.54.100)
avformat: YES (58.29.100)
avutil: YES (56.31.100)
swscale: YES (5.5.100)
avresample: YES (4.0.0)
GStreamer: YES (1.16.3)
v4l/v4l2: YES (linux/videodev2.h)
Parallel framework: TBB (ver 2020.1 interface 11101)
Trace: YES (with Intel ITT)
Other third-party libraries:
Intel IPP: 2020.0.0 Gold [2020.0.0]
at: /home/hb/Downloads/opencv-4.5.2/build/3rdparty/ippicv/ippicv_lnx/icv
Intel IPP IW: sources (2020.0.0)
at: /home/hb/Downloads/opencv-4.5.2/build/3rdparty/ippicv/ippicv_lnx/iw
VA: YES
Lapack: YES (/usr/lib/x86_64-linux-gnu/liblapack.so /usr/lib/x86_64-linux-gnu/libcblas.so /usr/lib/x86_64-linux-gnu/libatlas.so)
Eigen: YES (ver 3.3.7)
Custom HAL: NO
Protobuf: build (3.5.1)
NVIDIA CUDA: YES (ver 11.6, CUFFT CUBLAS FAST_MATH)
NVIDIA GPU arch: 86
NVIDIA PTX archs:
cuDNN: YES (ver 8.3.3)
Python 3:
Interpreter: /home/hb/anaconda3/bin/python3.7m (ver 3.7.6)
Libraries: /home/hb/anaconda3/lib/libpython3.7m.so (ver 3.7.6)
numpy: /home/hb/anaconda3/lib/python3.7/site-packages/numpy/core/include (ver 1.18.1)
install path: /home/hb/anaconda3/lib/python3.7/site-packages/cv2/python-3.7
Python (for build): /home/hb/anaconda3/bin/python3.7m
Java:
ant: /bin/ant (ver 1.10.7)
JNI: /usr/lib/jvm/java-8-openjdk-amd64/include /usr/lib/jvm/java-8-openjdk-amd64/include/linux /usr/lib/jvm/java-8-openjdk-amd64/include
Java wrappers: YES
Java tests: YES
Install to: /usr/local
-----------------------------------------------------------------
最后测试能否使用cuda，代码如下：
#读取图片
import cv2
frame=cv2.imread('test.jpg')
#上传到gpu进行处理
gpu_frame=cv2.cuda_GpuMat()
gpu_frame.upload(frame)
print(gpu_frame.cudaPtr())
#resize
gpu_resframe=cv2.cuda.resize(gpu_frame,(1024,512))
cpu_resfram=gpu_resframe.download()
print(cpu_resfram.shape)
如果输出正确，代表安装成功！！！
卸载build下：
sudo make uninstall
是不是挺简单呢。如果遇到任何问题，请及时评论！