Ubuntu20.04源码安装Opencv，保姆级教程少走90%的弯路
2023-09-21
前言
正文
最小依赖
sudo apt update
sudo apt install -y cmake g++ wget unzip
sudo apt-get install build-essential pkg-config libgtk2.0-dev libavcodec-dev libavformat-dev libjpeg-dev libswscale-dev libtiff5-dev
其他依赖
# 2. INSTALL THE DEPENDENCIES
# Build tools:
sudo apt-get install -y build-essential cmake
# GUI (if you want GTK, change 'qt5-default' to 'libgtkglext1-dev' and remove '-DWITH_QT=ON'):
sudo apt-get install -y qt5-default libvtk6-dev
# Media I/O:
sudo apt-get install -y zlib1g-dev libjpeg-dev libwebp-dev libpng-dev libtiff5-dev libjasper-dev \
libopenexr-dev libgdal-dev
# Video I/O:
sudo apt-get install -y libdc1394-22-dev libavcodec-dev libavformat-dev libswscale-dev \
libtheora-dev libvorbis-dev libxvidcore-dev libx264-dev yasm \
libopencore-amrnb-dev libopencore-amrwb-dev libv4l-dev libxine2-dev
# Parallelism and linear algebra libraries:
sudo apt-get install -y libtbb-dev libeigen3-dev
# Python:
sudo apt-get install -y python-dev python-tk pylint python-numpy \
python3-dev python3-tk pylint3 python3-numpy flake8
# Java:
sudo apt-get install -y ant default-jdk
# Documentation and other:
sudo apt-get install -y doxygen unzip wget
下载源码
下载opencv源码
git clone -b 4.9.0 https://github.com/opencv/opencv.git
下载opencv_contrib源码
cd opencv
git clone -b 4.9.0 https://github.com/opencv/opencv_contrib.git
编译
mkdir build
cd build
# cmake ..
cmake命令
cmake -D WITH_OPENGL=ON \
-D OPENCV_EXTRA_MODULES_PATH=../opencv_contrib/modules \
-D CMAKE_INSTALL_PREFIX=~/software/opencv \
-D CMAKE_BUILD_TYPE=RELEASE \
-D CUDNN_LIBRARY="/home/ai/dyb/cudnn-linux-x86_64-8.8.0.121_cuda12-archive/lib/libcudnn.so" \
-D CUDNN_INCLUDE_DIR="/home/ai/dyb/cudnn-linux-x86_64-8.8.0.121_cuda12-archive/include/cudnn.h" \
-D CUDA_ARCH_BIN=12.0 \
-D CUDNN_VERSION=8.8.0 \
-D WITH_TBB=ON \
-D WITH_V4L=ON \
-D WITH_GTK_2_X=ON \
-D WITH_CUDA=ON \
-D CUDA_GENERATION=Auto \
-D WITH_CUBLAS=1 \
-D WITH_GTK=ON \
-D ENABLE_FAST_MATH=1 \
-D CUDA_FAST_MATH=1 \
-D WITH_FFMPEG=ON \
-D OPENCV_GENERATE_PKGCONFIG=1 \
-D BUILD_opencv_cudacodec=ON \
-D WITH_QT=OFF \
-D WITH_GSTREAMER=ON \
-D WITH_CUDNN=ON \
-D OPENCV_DNN_CUDA=ON \
-D WITH_NVCUVID=ON ..
cmake -D WITH_OPENGL=ON \
-D OPENCV_EXTRA_MODULES_PATH=../opencv_contrib/modules \
-D CMAKE_INSTALL_PREFIX=~/software/opencv \
-D CMAKE_BUILD_TYPE=RELEASE \
-D WITH_TBB=ON \
-D WITH_V4L=ON \
-D WITH_GTK_2_X=ON \
-D WITH_CUDA=ON \
-D CUDA_GENERATION=Auto \
-D WITH_CUBLAS=1 \
-D WITH_GTK=ON \
-D ENABLE_FAST_MATH=1 \
-D CUDA_FAST_MATH=1 \
-D WITH_FFMPEG=ON \
-D OPENCV_GENERATE_PKGCONFIG=1 \
-D BUILD_opencv_cudacodec=ON \
-D WITH_QT=OFF \
-D WITH_GSTREAMER=ON \
-D WITH_CUDNN=ON \
-D OPENCV_DNN_CUDA=ON \
-D WITH_NVCUVID=ON .. \
-D CUDA_nvcuvid_LIBRARY=/home/ai/dyb/Video_Codec_SDK_12.0.16/Lib/linux/stubs/x86_64/libnvcuvid.so \
-D PYTHON3_EXECUTABLE=$(which python) \
-D BUILD_opencv_python3=ON \
-D PYTHON3_LIBRARY=/home/ai/anaconda3/pkgs/python-3.8.19-h955ad1f_0/lib/ \
-D PYTHON3_INCLUDE_DIR=/home/ai/anaconda3/envs/py38/include/python3.8/ \
-D PYTHON3_NUMPY_INCLUDE_DIRS=/home/ai/anaconda3/envs/py38/lib/python3.8/site-packages/numpy/core/include/ \
-D PYTHON3_PACKAGES_PATH=/home/ai/anaconda3/envs/py38/lib/python3.8/site-packages ..
注意：如果编译出来的Opencv不支持视频编解码，一般是FFmpeg没有成功安装，最终输出的信息因该是包含下面这样
-- 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)
编译，-j后面是cpu核心数，加快编译速度
make -j24
make install
然后就是漫长的等待，根据cpu核心数不同，等待时间不同，我电脑编译大概需要10分钟
常见错误
DNN: CUDA backend requires cuDNN. Please resolve dependency or disable
Could NOT find CUDNN: Found unsuitable version “…”, but required is at least “7.5”
遇到这个错误，安装cudnn或则设置OPENCV_DNN_CUDA=OFF,这个错误有可能是因为新版的cudnn已经把版本信息放到文件cudnn_version.h中,尝试修改cmake/FindCUDNN.cmake
下载地址：cudnn-download
如果错误没有解决,可尝试使用
sudo cp cudnn/include/* /usr/local/cuda-12.0/include/
sudo cp cudnn/lib/* /usr/local/cuda-12.0/lib64/
install Video_Codec_SDK_11.1.5.zip
https://blog.csdn.net/u014248312/article/details/127307407?ydreferer=aHR0cHM6Ly9jbi5iaW5nLmNvbS8%3D
sudo cp /Video_Codec_SDK_11.1.5/Interface/* /usr/local/cuda/include/
sudo cp /Video_Codec_SDK_11.1.5/Lib/linux/stubs/x86_64/* /usr/local/cuda/lib64/
Video_Codec_SDK
没有检测到视频Video_Codec_SDK，原来是版本不对，机器上安装的cuda 10.2，最新的SDK不匹配
下载历史版本： Video Codec SDK Archive | NVIDIA Developer
下载： Video_Codec_SDK_10.0.26.zip
cp ../data/Video_Codec_SDK_10.0.26/Interface/*.h /usr/local/cuda/include/
cp ../data/Video_Codec_SDK_10.0.26/Lib/linux/stubs/aarch64/*.so /usr/local/cuda/lib64/
GLIBCXX_3.4.29
undefined reference to `std::__throw_bad_array_new_length()@GLIBCXX_3.4.29’
strings /usr/lib/x86_64-linux-gnu/libstdc++.so.6 | grep GLIBCXX
sudo add-apt-repository ppa:ubuntu-toolchain-r/test # Ignore if not ubuntu
sudo apt-get update
sudo apt-get upgrade libstdc++6
python使用实例
import cv2
def main(file_path):
cv2.namedWindow("GPU", cv2.WINDOW_OPENGL)
cap = cv2.cudacodec.createVideoReader(file_path)
while True:
ret, frame = cap.nextFrame()
if ret is False:
break
cv2.imshow('image', frame)
cv2.waitKey(1)
cap.release()
if __name__ == '__main__':
file_path = 'test.mp4'
main(file_path)