OpenCV—Python Numpy数组（像素点）操作

一、遍历访问图片每个像素点，并修改相应的RGB

def access_pixels(image):
    print(image.shape)
    height = image.shape[0]
    width = image.shape[1]
    channels = image.shape[2]
    print("width: %s  height: %s  channels: %s"%(width, height, channels))
    for row in range(height):
        for col in range(width):
            for c in range(channels):
                pv = image[row , col, c]              #获取每个像素点的每个通道的数值
                image[row, col, c]=255 - pv           #灰度值是0-255   这里是修改每个像素点每个通道灰度值
    cv2.imshow("Reverse_phase_image",image)
    
if __name__ =="__main__":
    src=cv2.imread('555.png')                          #默认彩色读入
    cv2.imshow('original_image', src)                  #显示图像

    t1 = cv2.getTickCount()                            #GetTickcount函数返回从操作系统启动到当前所经过的毫秒数
    access_pixels(src)
    t2 = cv2.getTickCount()
    time = (t2-t1)/cv2.getTickFrequency()              #getTickFrequency函数返回CPU的频率,就是每秒的计时周期数
    print("time : %s ms"%(time*1000) )                 #输出运行时间
    cv2.waitKey(0)
    cv2.destroyAllWindows()