Ubuntu 24.04安裝OpenCV4和环境配置

安装cmake（编译器）和依赖库

sudo apt install cmake gcc g++

支持python

sudo apt install -y python3-dev python3-numpy
sudo apt install -y libavcodec-dev libavformat-dev libswscale-dev libgstreamer-plugins-base1.0-dev libgstreamer1.0-dev libgtk2.0-dev libgtk-3-dev libpng-dev  libjpeg-dev libopenexr-dev libtiff-dev libwebp-dev

下载源文件

git clone https://github.com/opencv/opencv
git clone https://github.com/opencv/opencv_contrib

進入opencv的文件夾创建一个编译文件夹build，并进入

mkdir build && cd build/

開始make

cmake -D CMAKE_BUILD_TYPE=RELEASE \
      -D CMAKE_INSTALL_PREFIX=/usr \
      -D INSTALL_C_EXAMPLES=ON \
      -D INSTALL_PYTHON_EXAMPLES=ON \
      -D WITH_FFMPEG=ON \
      -D WITH_GTK=ON \
      -D PYTHON_DEFAULT_EXECUTABLE=/usr/bin/python3.12 \
      -D PYTHON_INCLUDE_DIR=/usr/include/python3.12 \
      -D OPENCV_GENERATE_PKGCONFIG=ON \
      -D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib/modules \
      -D BUILD_EXAMPLES=ON ..

進行make編譯

make -j16
sudo make install

(可選項) 如果需要opencv的cuda功能，請用下面的指令make，但是會時間非常久!!!

cmake -D CMAKE_BUILD_TYPE=RELEASE \
      -D CMAKE_INSTALL_PREFIX=/usr \
      -D INSTALL_C_EXAMPLES=ON \
      -D INSTALL_PYTHON_EXAMPLES=ON \
      -D WITH_FFMPEG=ON \
      -D WITH_CUDA=ON \
      -D CUDA_FAST_MATH=1 \
      -D WITH_CUBLAS=1 \
      -D WITH_OPENGL=ON \
      -D OPENCV_GENERATE_PKGCONFIG=ON \
      -D OPENCV_ENABLE_NONFREE=ON \
      -D WITH_GTK=ON \
      -D PYTHON_DEFAULT_EXECUTABLE=/usr/bin/python3.12 \
      -D PYTHON_INCLUDE_DIR=/usr/include/python3.12 \
      -D OPENCV_DNN_CUDA=ON \
      -D CUDA_ARCH_BIN=8.6 \
      -D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib/modules \
      -D BUILD_EXAMPLES=ON ..

因爲我這裡的python是選擇安裝啊Anaconda3的目錄下，請自行修改，另外根據你自己的GPU選擇適合的CUDA_ARCH_BIN，RTX 3090可以選擇8.6

配置環境

將opencv4.pc文件複製到pkgconfig文件夾裡

sudo cp /usr/lib/x86_64-linux-gnu/pkgconfig/opencv4.pc /usr/lib/pkgconfig/

簡述configure、pkg-config、pkg_config_path三者的關係-软件开发平台及语言笔记大全(超详细)

下面可以直接去測試看看了，如果不行再做下面剩下的測試

$ sudo find / -iname opencv4.pc
/usr/lib/x86_64-linux-gnu/pkgconfig/opencv4.pc
/usr/lib/pkgconfig/opencv4.pc
/usr/local/lib/pkgconfig/opencv4.pc
find: ‘/run/user/1000/gvfs’: Permission denied

将/usr/local/lib/pkgconfig/路径加入PKG_CONFIG_PATH：

$ sudo vim /etc/profile.d/pkgconfig.sh

在文件中加入下面一行：

export
 PKG_CONFIG_PATH=/usr/local/lib/pkgconfig:$PKG_CONFIG_PATH

保存退出后，使用命令激活：

$source /etc/profile

验证是否配置成功：

$ pkg-config --libs opencv4
-L/usr/local/lib -lopencv_gapi -lopencv_stitching -lopencv_alphamat -lopencv_aruco -lopencv_bgsegm -lopencv_bioinspired -lopencv_ccalib -lopencv_dnn_objdetect -lopencv_dnn_superres -lopencv_dpm -lopencv_face -lopencv_freetype -lopencv_fuzzy -lopencv_hdf -lopencv_hfs -lopencv_img_hash -lopencv_intensity_transform -lopencv_line_descriptor -lopencv_mcc -lopencv_quality -lopencv_rapid -lopencv_reg -lopencv_rgbd -lopencv_saliency -lopencv_stereo -lopencv_structured_light -lopencv_phase_unwrapping -lopencv_superres -lopencv_optflow -lopencv_surface_matching -lopencv_tracking -lopencv_highgui -lopencv_datasets -lopencv_text -lopencv_plot -lopencv_videostab -lopencv_videoio -lopencv_viz -lopencv_xfeatures2d -lopencv_shape -lopencv_ml -lopencv_ximgproc -lopencv_video -lopencv_dnn -lopencv_xobjdetect -lopencv_objdetect -lopencv_calib3d -lopencv_imgcodecs -lopencv_features2d -lopencv_flann -lopencv_xphoto -lopencv_photo -lopencv_imgproc -lopencv_core

动态库环境

配置OpenCV动态库环境 — — 程序执行时加载动态库*.so的路径。

$ sudo vim /etc/ld.so.conf.d/opencv4.conf

在该文件（可能是空文件）末尾加上：

/usr/local/lib

再执行以下命令使刚才配置的路径生效：

$ sudo ldconfig

python-opencv环境
找到编译好的python cv库：

$ sudo find / -iname cv2*.so
/usr/lib/python3.12/site-packages/cv2/python-3.12/cv2.cpython-312-x86_64-linux-gnu.so

cv2.cpython-312m-x86_64-linux-gnu.so就是編譯好的python3的opencv庫，把它複製到python解释器/path/to/site-packages目錄下，之後就可以在該python解釋器中使用python-opencv了。

鏈接到Anaconda創建的python3解釋器中：

$ ln -s /usr/lib/python3.12/dist-packages/cv2/python-3.12/cv2.cpython-312-x86_64-linux-gnu.so ~/anaconda3/lib/python3.12/site-packages/cv2.so

测试OpenCV

cd 到/opencv/samples/cpp/example_cmake目录下，查看当前目录内容：

$ mkdir build && cd build
$ cmake ..
$ make
$ ./opencv_example