02灰度处理2

方法3 求均值法

import cv2
import numpy as np
img = cv2.imread('image0.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]

# RGB R=G=B = gray  (R+G+B)/3 
#让三个通道完全相等，将RBG值的均值作为当前值，就可获得灰度图

dst = np.zeros((height,width,3),np.uint8)
for i in range(0,height):
    for j in range(0,width):
        (b,g,r) = img[i,j]
        gray = (int(b)+int(g)+int(r))/3 #防止计算溢出255，先转换为int再计算
        dst[i,j] = np.uint8(gray)  #转换回去
cv2.imshow('dst',dst)
cv2.waitKey(0)

方法4 gray = r0.299+g0.587+b*0.114

import cv2
import numpy as np
img = cv2.imread('image0.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]

dst = np.zeros((height,width,3),np.uint8)
for i in range(0,height):
    for j in range(0,width):
        (b,g,r) = img[i,j]
        b = int(b)      #先转换,再计算
        g = int(g)
        r = int(r)
        gray = r*0.299+g*0.587+b*0.114
        dst[i,j] = np.uint8(gray)
cv2.imshow('dst',dst)
cv2.waitKey(0)