How to build an OpenCV and Python environment

Open Source Computer Vision Library.OpenCV was established by Intel in 1999 and is now supported by Willow Garage. OpenCV is a cross-platform computer vision library released under the BSD license (open source) and can run on Linux, Windows, and MacOS operating systems. It is lightweight and efficient - it consists of a series of C functions and a small number of C classes. It also provides interfaces in Python, Ruby, MATLAB and other languages, and implements many common algorithms in image processing and computer vision. The latest version is 3.1, released on January 29, 2016.

#In short, openCV can be used to edit computer images and videos. It is widely used in image recognition, motion tracking, machine vision and other fields.

After everything is ready, run cmd or PowerShell as administrator. Enter the following commands in sequence: (Recommended learning: Python video tutorial)

pip install --upgrade setuptools
pip install numpy Matplotlib
pip install opencv-python

The opencv environment has been completed, it is that simple. It only requires three packages: numpy, Matplotlib, and opencv-python. It can be downloaded quickly and easily. If an error or wrong occurs during downloading, just re-enter the command.

Test

#导入cv模块
import cv2 as cv
#读取图像，支持 bmp、jpg、png、tiff 等常用格式
img = cv.imread("D:\python\test.jpg")
#创建窗口并显示图像
cv.namedWindow("Image")
cv.imshow("Image",img)
cv.waitKey(0)
#释放窗口
cv2.destroyAllWindows()

Run the above script. If the test image can be displayed, the environment is set up successfully.

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