计算机视觉：图片的灰度处理和颜色反转

Posted 2021-12-22 il_持之以恒_li

1.灰度处理

1.1 方法1

还记得我的这篇博客的这个注释吗？

也就是方法cv2.imread()，里面有两个参数，第一个参数为图片的路径，第二个参数为是否为彩色图片，如果把第二个参数改为0，会怎么样呢？

import cv2

# 方法1
img = cv2.imread(filename='../anqila21.jpg',flags=0)
cv2.imshow('demo',img)
cv2.waitKey(0)

1.2 方法2

import cv2

# 方法2
img = cv2.imread(filename='../anqila21.jpg',flags=1)
dst = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
cv2.imshow('demo',dst)
cv2.waitKey(0)

运行结果和上述一样

1.3 方法3 使用算法实现

import cv2
import numpy as np

# 算法实现
img = cv2.imread(filename='../anqila21.jpg',flags=1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
dst = np.zeros((height,width,3),np.uint8)
for i in range(height):
    for j in range(width):
        (b,g,r) = img[i,j]
        # gray = (int(b)+int(g)+int(r))/3 # 灰度值
        # dst[i,j] = np.uint8(gray)

        gray = 0.299*int(r)+0.587*int(g)+0.114*int(b) # 灰度值
        dst[i,j] = np.uint8(gray)
cv2.imshow('demo',dst)
cv2.waitKey(0)

2. 图片的颜色反转

2.1 灰度图片的颜色反转

import cv2
import numpy as np

img = cv2.imread(filename='../anqila21.jpg',flags=0)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
dst = np.zeros((height,width),np.uint8)
for i in range(height):
    for j in range(width):
        gray = img[i,j]
        dst[i,j] = 255-gray

cv2.imshow('dst',dst)
cv2.waitKey(0)

2.2 彩色图片的颜色反转

import cv2
import numpy as np


img = cv2.imread(filename='../anqila21.jpg',flags=1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
dst = np.zeros((height,width,3),np.uint8)
for i in range(height):
    for j in range(width):
        (b,g,r) = img[i,j]
        dst[i,j] = (255-b,255-g,255-r)

cv2.imshow('dst',dst)
cv2.waitKey(0)