4-4 算法优化

# 1 灰度 最重要 2 基础 3 实时性
# 定点-》浮点 +- */ >>
# r*0.299+g*0.587+b*0.114

import cv2
import numpy as np
img = cv2.imread('image0.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
# RGB R=G=B = gray (R+G+B)/3
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]
         # 浮点转定点
        b = int(b)
        g = int(g)
        r = int(r)
        gray = (r*1+g*2+b*1)/4
         #gray = (int(b)+int(g)+int(r))/3
        dst[i,j] = np.uint8(gray)
cv2.imshow('dst',dst)
cv2.waitKey(0)

# 1 灰度 最重要 2 基础 3 实时性
# 定点-》浮点 +- */ >>
# r*0.299+g*0.587+b*0.114

import cv2
import numpy as np
img = cv2.imread('image0.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
# RGB R=G=B = gray (R+G+B)/3
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]
         # 浮点转定点
        b = int(b)
        g = int(g)
        r = int(r)
        #gray = (r*1+g*2+b*1)/4
        gray = (int(b)+int(g)+int(r))/3
        dst[i,j] = np.uint8(gray)
cv2.imshow('dst',dst)
cv2.waitKey(0)

# 1 灰度 最重要 2 基础 3 实时性
# 定点-》浮点 +- */ >>
# r*0.299+g*0.587+b*0.114

import cv2
import numpy as np
img = cv2.imread('image0.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
# RGB R=G=B = gray (R+G+B)/3
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]
         # 浮点转定点
        b = int(b)
        g = int(g)
        r = int(r)
        #gray = (r*1+g*2+b*1)/4
        # 定点转移位
        gray = (r+(g<<1)+b)>>2
        #gray = (int(b)+int(g)+int(r))/3
        dst[i,j] = np.uint8(gray)
cv2.imshow('dst',dst)
cv2.waitKey(0)

# 1 灰度 最重要 2 基础 3 实时性
# 定点-》浮点 +- */ >>
# r*0.299+g*0.587+b*0.114
# 100 1000 10000
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
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]
         # 浮点转定点
        b = int(b)
        g = int(g)
        r = int(r)
        #gray = (r*1+g*2+b*1)/4
        # 定点转移位
        gray = (r+(g<<1)+b)>>2
        #gray = (int(b)+int(g)+int(r))/3
        dst[i,j] = np.uint8(gray)
cv2.imshow('dst',dst)
cv2.waitKey(0)