opencv(3)图像像素取反

1.图像取反

import cv2 as cv


# 索引是[i,j,k] 这样写的 而不是[i:j:k] 这样写的
def access_pixels(img):
    s = img.shape
    for i in range(s[0]):
        for j in range(s[1]):
            for k in range(s[2]):
                # print(i, j, k)
                pv = img[i, j, k]
                img[i, j, k] = 255 - pv
    # cv.imshow("input", img)
    # cv.imwrite("leda_covert.jpg", img)
    # cv.waitKey(0)
    # cv.destroyAllWindows()


if __name__ == "__main__":
    src = cv.imread("leda.jpg")
    t1 = cv.getTickCount()
    access_pixels(src)
    t2 = cv.getTickCount()
    time = (t2-t1)/cv.getTickFrequency()
    print(time)

2. 调用api使用非操作实现色彩值取反

import cv2 as cv
def invert():
    img = cv.imread("leda.jpg")
    dst = cv.bitwise_not(img)
    cv.imshow("input",dst)
    cv.waitKey(0)
    cv.destroyAllWindows()
if __name__ == "__main__":
    invert()

3. 色彩空间的转换

import cv2 as cv

#分别把图象转化成 rgb gray hsv三种三踩空间并展示
def color_space(img):
   rgb = cv.cvtColor(img,cv.COLOR_BGR2RGB)
   cv.namedWindow("RGB",cv.WINDOW_AUTOSIZE)
   cv.imshow("RGB",rgb)
   gray = cv.cvtColor(img,cv.COLOR_BGR2GRAY)
   cv.namedWindow("gray", cv.WINDOW_AUTOSIZE)
   cv.imshow("gray",gray)
   hsv = cv.cvtColor(img,cv.COLOR_BGR2HSV)
   cv.namedWindow("hsv", cv.WINDOW_AUTOSIZE)
   cv.imshow("hsv",hsv)


if __name__ == "__main__":
   src = cv.imread("leda.jpg")
   color_space(src)
   cv.waitKey(0)
   cv.destroyAllWindows()

4. RGB通道分离与合并

 import cv2 as cv

def split_channel(img):
   b,g,r = cv.split(img)
   cv.namedWindow("b", cv.WINDOW_AUTOSIZE)
   cv.imshow("b", b)
   cv.namedWindow("g", cv.WINDOW_AUTOSIZE)
   cv.imshow("g", g)
   cv.namedWindow("r", cv.WINDOW_AUTOSIZE)
   cv.imshow("r",r)
   src = cv.merge([b,g,r])
   cv.namedWindow("src", cv.WINDOW_AUTOSIZE)
   cv.imshow("src", src)

if __name__ == "__main__":
   src = cv.imread("leda.jpg")
   split_channel(src)
   cv.waitKey(0)
   cv.destroyAllWindows()

5. 自定义三通道图像

import cv2 as cv
import numpy as np


def create_img():
   src = np.zeros([400, 400, 3],np.uint8)
   src[:, :, 0] = np.ones([400, 400]) * 255
   src[:, :, 1] = np.ones([400, 400]) * 255
   src[:, :, 2] = np.ones([400, 400]) * 255
   src1 = np.zeros([400,400,1],np.uint8)
   src1[:,:,0] = np.ones([400,400])*127
   # print(src.shape)
   cv.imshow("src", src)
   cv.imshow("src1", src1)


if __name__ == "__main__":
   create_img()
   cv.waitKey(0)
   cv.destroyAllWindows()