import cv2 as cv
import numpy as np
# 将图像中的像素值改为 255-原像素值
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))
# 三层循环逐个修改像素点
for row in range(height):
for col in range(width):
for c in range(channels):
pv = image[row, col, c]
image[row, col, c] = 255-pv
cv.imshow('pixel_demo', image)
# 作用等同于上面的access_pixels
def inverse(image):
dst = cv.bitwise_not(image)
cv.imshow('inverse demo', dst)
# 创建三通道、单通道图像
def creat_demo():
# img = np.zeros([400, 400, 3], np.uint8) # 三通道顺序是BGR
# # img[:, :, 0] = np.ones([400, 400]) * 255
# img[:, :, 2] = np.ones([400, 400])*255
# cv.imshow('new image', img)
#单通道
# img = np.ones([400, 400, 1], np.uint8) # 需要指明通道数1
# # img[:, :, 0] = np.ones([400, 400]) * 127
# img = img*127
# cv.imshow('new image', img)
# cv.imwrite('C:/Users/Y/Pictures/Saved Pictures/myImage.png', img)
m1 = np.ones([3, 3], np.uint8)
m1.fill(12222.388)
print(m1)
m2 = m1.reshape([1, 9])
print(m2)
src = cv.imread('C:/Users/Y/Pictures/Saved Pictures/demo.png')
cv.namedWindow('input image', cv.WINDOW_AUTOSIZE)
cv.imshow('input image', src)
t1 = cv.getTickCount()
inverse(src)
t2 = cv.getTickCount()
time = (t2-t1)/cv.getTickFrequency()
print('time: %s ms' % time*1000)
cv.waitKey(0)
cv.destroyAllWindows()import cv2 as cv
import numpy as np
# 将图像中的像素