1. OpenCV Introduction
OpenCV is a popular open source computer vision library, which provides many functions and implements many computer vision algorithms, ranging from the most basic filtering to advanced object detection. The design goal of OpenCV is to execute as fast as possible, focusing on real-time applications. It is written in optimized C/C++ code and can take full advantage of multi-core processors. Its main goal is to build a simple and easy-to-use computer vision framework to help Developers can more easily design more complex computer vision related applications.
OpenCV was founded by Intel in 1999 and is now supported by Willow Garage. It is a cross-platform computer vision library based on open source distribution, which can run on Linux, Windows, Mac OS, Android, iOS, Maemo, FreeBSD, OpenBSD and other operating systems.
OpenCV can be used to solve problems in the following areas: Human-computer interaction, object recognition, image partitioning, face recognition, motion recognition, motion tracking
2. Install OpenCV
1. First install the necessary software and dependent libraries, etc.
sudo apt-get update sudo apt-get install cmake git sudo apt-get install cmake qt5-default libvtk6-dev zlib1g-dev libjpeg-dev libwebp-dev libpng-dev libtiff5-dev libopenexr-dev libgdal-dev libdc1394-22-dev libavcodec-dev libavformat-dev libswscale-dev libtheora-dev libvorbis-dev libxvidcore-dev libx264-dev yasm libopencore-amrnb-dev libopencore-amrwb-dev
2 Download the OpenCV source code
On the OpenCV official website https://opencv.org/releases/ select the version and download method you need to download。
The version used here is OpenCV–4.2.0.
cd opencv-4.2.0 mkdir build cd build cmake -D CMAKE_BUILD_TYPE=RELEASE -D \ CMAKE_INSTALL_PREFIX=/usr/local/opencv .. make -j4 make install ldconfig
Simple test example
import cv2 as cv img = cv.imread("/usr/share/lxde/wallpapers/orangepi.jpg") cv.namedWindow("Image") cv.imshow("Image", img) cv.waitKey(0) cv.destroyAllWindows()