【OpenCV】灰度算法[API与源码实现]

• • • • • 导读
• API调用
• • API调用法1 ----> imread 传参
  • API调用法2 ----> cvtColor 函数
• 源码实现
• • 源码实现法1 ----> 均值法
  • 源码实现法2 ----> 心理学公式
• 算法优化

1. API调用（2个方法）
2. 源码实现法（2个方法）

import cv2
import numpy as np


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

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)

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)

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)

1. 整型 速度快于 浮点型
2. ±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)