API调用

API调用法1 —-> imread 改参

import cv2
import numpy as np


img = cv2.imread("../01_Img/01.jpg", 0)
cv2.imshow("", img)
cv2.waitKey(0)

API调用法2 —-> cvtColor 函数

import cv2
import numpy as np

# 方法2 ----> cvtColor 函数
img = cv2.imread("../01_Img/01.jpg", 1)
dst = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

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

源码实现

源码实现法1 —-> 均值法

import cv2
import numpy as np

img = cv2.imread("../01_Img/01.jpg", 1)
imgInfo = img.shape
dst = np.zeros((imgInfo[0], imgInfo[1], imgInfo[2]), np.uint8)

for i in range(0, imgInfo[0]):
    for j in range(0, imgInfo[1]):
        (b, g, r) = img[i, j]
        gray = (int(b)+int(g)+int(r))/3
        dst[i, j] = (gray, gray, gray)

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

源码实现法2 —-> 心理学法

import cv2
import numpy as np
# 心理学法：gray = r*0.299+g*0.587+b*0.114

img = cv2.imread("../01_Img/01.jpg", 1)
imgInfo = img.shape
dst = np.zeros((imgInfo[0], imgInfo[1], imgInfo[2]), np.uint8)

for i in range(0, imgInfo[0]):
    for j in range(0, imgInfo[1]):
        (b, g, r) = img[i, j]
        gray = r * 0.299 + g * 0.587 + b * 0.114
        dst[i, j] = (gray, gray, gray)

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

算法优化

整型速度快于浮点型
+-运算速度快于 */运算
```
 import cv2
 import numpy as np
```

    img = cv2.imread("../01_Img/01.jpg", 1)
    imgInfo = img.shape
    dst = np.zeros((imgInfo[0], imgInfo[1], imgInfo[2]), np.uint8)

    for i in range(0, imgInfo[0]):
        for j in range(0, imgInfo[1]):
            (b, g, r) = img[i, j]
            # gray = (r * 1 + g * 2 + b * 1)/4
            gray = (r + (g<<1) + b) >> 2
            dst[i, j] = (gray, gray, gray)

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