OpenCV-python 常见用法 · 个人总结

ゝ一纸荒年。 2021-12-17 02:19 294阅读 0赞

今天给自己总结一下 python openCV 的一些常见用法。

包括

1. 显示原图

2. 显示灰度图

3. GRB通道分离

4. 坐标旋转

5. 重定义大小

6. 图像裁剪

7. 亮度增强

8. 直方图均衡

9. 滤波

10. 边缘检测

11. 角点检测

#coding: utf-8
    import cv2
    import numpy as np
    
    #原图显示
    im = cv2.imread("star.jpg")
    cv2.imshow("pic.jpg", im)
    cv2.waitKey(0)
    
    #灰度值显示
    gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
    cv2.imshow("gray.jpg", gray)
    cv2.waitKey(0)
    
    #BGR通道分离
    (B, G, R) = cv2.split(im)
    cv2.imshow("Red", R)
    cv2.imshow("Green", G)
    cv2.imshow("Blue", B)
    cv2.waitKey(0)
    
    #坐标旋转
    rows, cols, channel = im.shape
    M = cv2.getRotationMatrix2D(((cols-1)/2.0, (rows-1)/2.0), 90, 1)
    dst = cv2.warpAffine(im, M, (cols, rows))
    cv2.imshow("dst", dst)
    dst = cv2.flip(im, 1)   #水平翻转
    dst = cv2.flip(im, 0)   #垂直翻转
    dst = cv2.flip(im, -1)  #水平垂直翻转
    cv2.waitKey(0)
    
    #resize
    res = cv2.resize(im, None, fx=2, fy=0.5, interpolation = cv2.INTER_CUBIC)
    cv2.imshow("res", res)
    cv2.waitKey(0)
    
    #图像裁剪
    im1 = im[200:500, 300:600]  #(y0:y1, x0:x1)
    cv2.imshow("im1", im1)
    cv2.waitKey(0)
    
    #亮度增强
    res1 = np.uint8(np.clip(1.5*im,0,255))
    res2 = np.uint8(np.clip(0.7*im,0,255))
    tmp1 = np.hstack((im, res1, res2))
    cv2.imshow("image", tmp1)
    cv2.waitKey(0)
    
    #暂时跳过饱和度、对比度、锐度增强
    #直方图均衡
    gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
    equalize = cv2.equalizeHist(gray)
    cv2.imshow('equalize', equalize)
    cv2.waitKey(0)
    
    #滤波
    blur = cv2.blur(im, (5,5))                      #均值平滑滤波
    gauss = cv2.GaussianBlur(im, (5,5), 0)          #高斯滤波
    median = cv2.medianBlur(im, 5)                  #中值滤波
    bilateral = cv2.bilateralFilter(im, 9, 5, 5)    #双边滤波
    filt = np.hstack([blur, gauss, median, bilateral])
    cv2.imshow("filter", filt)
    cv2.waitKey(0)
    
    #边缘检测
    gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
    _, binary = cv2.threshold(gray,127,255,cv2.THRESH_BINARY)
    contours, hierarchy = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    con = cv2.drawContours(im,contours,-1,(0,0,255),3)
    cv2.imshow("con", con)
    cv2.waitKey(0)
    
    #角点检测
    gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
    dst = cv2.cornerHarris(gray,5,5,0.04)
    dst = cv2.dilate(dst,None)#图像膨胀
    im[dst>0.01*dst.max()]=[0,0,255]
    cv2.imshow('dst',im)
    cv2.waitKey(0)
    cv2.destroyAllWindows()