python opencv关闭窗口 python中opencv的用法

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2

# 接收两个参数，一个是文件名，一个值，如果值为1，接收的是彩色图片，如果值为零，接受的是灰度图片。会有一个返回值，表示返回的图片内容

img = cv2.imread('mashiro.jpg',1)

# 接收两个参数，一个是窗体名称，另一个是要显示的内容

cv2.imshow('mashiro',img)

# 将程序暂停，只有这样，才能看到图片,否则图片会一闪而过因为程序结束了，如果time.sleep()的话，会卡住

cv2.waitKey(0)

2. 图片写入

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
img = cv2.imread('mashiro.jpg',1)
cv2.imwrite('mashiro1.jpg',img)

3.不同图片质量保存

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
img = cv2.imread('mashiro.jpg',1)
cv2.imwrite('mashiro1.jpg',img,[cv2.IMWRITE_JPEG_QUALITY,0])
cv2.imwrite('mashiro2.png',img,[cv2.IMWRITE_PNG_COMPRESSION,0])

# jpg属于有损压缩，是以图片的清晰度为代价的，数字越小，压缩比越高，图片质量损失越严重

# png属于无损压缩，数字0-9，数字越低，压缩比越低

4.像素操作基础

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
img = cv2.imread('mashiro.jpg',1)
(a,b,c) = img[500,500]
print(a,b,c)
for i in range(1,100):
 img[i,i] = (255,0,0)
cv2.imshow('mashiro',img)
cv2.waitKey(0)

5.图片缩放

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
img = cv2.imread('mashiro.jpg',1)
cv2.imshow('mashiro',img)
imginfo = img.shape
height = imginfo[0]
width = imginfo[1]
mode = imginfo[2]
print(imginfo)
dstHeight = int(height*0.5)
dstWidth = int(width*0.5)
dst = cv2.resize(img,(dstWidth,dstHeight))
cv2.imshow('mashiro1',dst)
cv2.waitKey(0)

6.图片缩放（源码实现）

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
import numpy as np
img = cv2.imread('mashiro.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
dstHeight = int(height/2)
dstWidth = int(width/2)
dstImage = np.zeros((dstHeight,dstWidth,3),np.uint8)
for i in range(0,dstHeight):
for j in range(0,dstWidth):
iNew = int(i*(height*1.0/dstHeight))
jNew = int(j*(width*1.0/dstWidth))
 dstImage[i,j] = img[iNew,jNew]
cv2.imshow('mashiro',dstImage)
cv2.waitKey(0)

7.图片剪切

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
img = cv2.imread('mashiro.jpg',1)
imgInfo = img.shape
dst = img[10:600,10:400]
cv2.imshow('mashiro',dst)
cv2.waitKey(0)

8.图片移位

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2,numpy as np
img = cv2.imread('mashiro.jpg',1)
cv2.imshow('mashiro',img)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
matshift = np.float32([[1,0,100],[0,1,200]])
dst = cv2.warpAffine(img,matshift,(height,width))
cv2.imshow('mashiro1',dst)
cv2.waitKey(0)

9.图片移位（源码实现）

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
import numpy as np
img = cv2.imread('mashiro.jpg',1)
imgInfo = img.shape
cv2.imshow('mashiro',img)
dst = np.ones(imgInfo,np.uint8)
height = imgInfo[0]
width = imgInfo[1]
for i in range(0,height):
for j in range(0,width-300):
 dst[i,j] = img[i,j]
cv2.imshow('mashiro1',dst)
cv2.waitKey(0)

10.图片镜像

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
import numpy as np
img = cv2.imread('mashiro.jpg',1)
imgInfo = img.shape
cv2.imshow('mashiro',img)
dst = np.ones(imgInfo,np.uint8)
height = imgInfo[0]
width = imgInfo[1]
for i in range(0,height):
for j in range(0,width):
 dst[i,j] = img[height-1-i,j]
cv2.imshow('mashiro1',dst)
cv2.waitKey(0)

11.图片仿射变换

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
import numpy as np
img = cv2.imread('mashiro.jpg',1)
cv2.imshow('mashiro',img)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
matSrc = np.float32([[0,0],[0,height-1],[width-1,0]])
matDst = np.float32([[50,50],[300,height-200],[width-300,100]])
matAffine = cv2.getAffineTransform(matSrc,matDst)
dst = cv2.warpAffine(img,matAffine,(width,height))
cv2.imshow('mashiro1',dst)
cv2.waitKey(0)

12.图片旋转

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
import numpy as np
img = cv2.imread('mashiro.jpg',1)
imgInfo = img.shape
cv2.imshow('mashiro',img)
height = imgInfo[0]
width = imgInfo[1]
matRotate = cv2.getRotationMatrix2D((width*0.5,height*0.5),45,0.5)
dst = cv2.warpAffine(img,matRotate,(width,height))
cv2.imshow('mashiro1',dst)
cv2.waitKey(0)

13.闲的蛋疼（批量将图片进行上述操作）

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
import glob
import numpy as np
all_jpg = glob.glob(r'C:\Users\Administrator\Desktop\satori\*.jpg')
for count,jpg in enumerate(all_jpg):
 img = cv2.imread(jpg,1)
 imgInfo = img.shape
 height = imgInfo[0]
 width = imgInfo[1]
 dst = cv2.resize(img,(int(width/2),int(height/2)))
cv2.imwrite(rf'C:\Users\Administrator\Desktop\satori\scale\{count}.jpg',dst,[cv2.IMWRITE_JPEG_QUALITY,100])
cv2.waitKey(0)
#######################################
for count,jpg in enumerate(all_jpg):
 img = cv2.imread(jpg,1)
 imgInfo = img.shape
 height = imgInfo[0]
 width = imgInfo[1]
matshift = np.float32([[1,0,100],[0,1,50]])
 dst = cv2.warpAffine(img,matshift,(width,height))
cv2.imwrite(rf'C:\Users\Administrator\Desktop\satori\translation\{count}.jpg',dst)
cv2.waitKey(0)
############################
for count,jpg in enumerate(all_jpg):
 img = cv2.imread(jpg,1)
 imgInfo = img.shape
 height = imgInfo[0]
 width = imgInfo[1]
 dst = np.zeros(imgInfo,np.uint8)
for i in range(0,height):
for j in range(0,width):
 dst[i,j] = img[height-1-i,j]
cv2.imwrite(rf'C:\Users\Administrator\Desktop\satori\flip\{count}.jpg',dst)
#######################
for count,jpg in enumerate(all_jpg):
 img = cv2.imread(jpg,1)
 imgInfo = img.shape
 height = imgInfo[0]
 width = imgInfo[1]
matsrc = np.float32([[0,0],[0,height-1],[width-1,0]])
matdst = np.float32([[50,50],[int(width/2),int(height/2)],[width-100,height-50]])
matAffine = cv2.getAffineTransform(matsrc,matdst)
 dst = cv2.warpAffine(img,matAffine,(width,height))
cv2.imwrite(rf'C:\Users\Administrator\Desktop\satori\shear\{count}.jpg',dst)
########################
for count,jpg in enumerate(all_jpg):
 img = cv2.imread(jpg,1)
 imgInfo = img.shape
 height = imgInfo[0]
 width = imgInfo[1]
matRotate = cv2.getRotationMatrix2D((width*0.5,height*0.5),60,0.5)
 dst = cv2.warpAffine(img,matRotate,(width,height))
cv2.imwrite(rf'C:\Users\Administrator\Desktop\satori\rotation\{count}.jpg',dst)

14.灰度处理

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2,numpy as np
img = cv2.imread('mashiro.jpg',0)
cv2.imshow('mashiro',img)
img = cv2.imread('b.png',1)
dst = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
cv2.imshow('mmp',dst)
cv2.waitKey(0)
img =cv2.imread('mashiro.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]
gray = (int(b)+int(g)+int(r))/3
dst[i,j] = [np.uint8(gray),np.uint8(gray),np.uint8(gray)]
cv2.imshow('mmp',dst)
cv2.waitKey(0)
img =cv2.imread('mashiro.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)
g = int(g)
r = int(r)
gray = r*0.9+b*0.87+r*0.4
dst[i,j] = [np.uint8(gray),np.uint8(gray),np.uint8(gray)]
cv2.imshow('mashiro1',dst)
cv2.waitKey(0)

15.颜色反转

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import numpy as np
import cv2
img = cv2.imread('mashiro.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
dst = np.zeros((height,width,1),np.uint8)
for i in range(0,height):
for j in range(0,width):
dst[i,j] = 255 - gray[i,j]
cv2.imshow('mashiro',gray)
cv2.imshow('mashiro1',dst)
cv2.waitKey(0)
# img = cv2.imread('mashiro.jpg',1)
# imgInfo = img.shape
# height = imgInfo[0]
# width = imgInfo[1]
# #gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
#
# 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]
# dst[i,j] = 255-b,255-g,255-r
#
# cv2.imshow('mashiro',img)
# cv2.imshow('mashiro1',dst)
# cv2.waitKey(0)

16.马赛克

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
import numpy as np
img = cv2.imread('mashiro.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
for m in range(200,400):
for n in range(100,200):
if m%10==0 and n%10==0:
for i in range(0,10):
for j in range(0,10):
 b,g,r = img[m,n]
 img[i+m,j+n] = b,g,r
cv2.imshow('mashiro',img)
cv2.waitKey(0)

17.毛玻璃

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import numpy as np
import cv2,random
img = cv2.imread('mashiro.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
dst = np.zeros((height,width,3),np.uint8)
mm = 8
for m in range(0,height-mm):
for n in range(0,width-mm):
index = int(random.random()*8)
 b,g,r = img[m+index,n+index]
dst[m,n] = b,g,r
cv2.imshow('mashiro',dst)
cv2.waitKey(0)

19.图片融合

import cv2
import numpy as np
img = cv2.imread('mashiro.jpg',1)
img1 = cv2.imread('mashiro.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
roiH = int(height/2)
roiW = int(width/2)
imgROI = img[0:roiH,0:roiW]
img1ROI = img[0:roiH,0:roiW]
dst = np.zeros((roiH,roiW,3),np.uint8)
dst = cv2.addWeighted(imgROI,0.5,img1ROI,0.5,0)
cv2.imshow('mashiro',dst)
cv2.waitKey(0)

# 貌似程序有问题

20.边缘检测

import cv2

import numpy as np

import random

# 所有边缘检测都是基于灰度处理的，因此先要转换成灰度图片

img = cv2.imread('mashiro.jpg',1)

imgInfo = img.shape

height = imgInfo[0]

width = imgInfo[1]

cv2.imshow('mashiro',img)

# 1 灰度

gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

# 2 高斯滤波

imgG = cv2.GaussianBlur(gray,(3,3),0)

# 图片经过卷积

dst = cv2.Canny(imgG,50,50)

cv2.imshow('mashiro1',dst)

cv2.waitKey(0)

21.浮雕效果

import cv2
import numpy as np
img = cv2.imread('mashiro.jpg',1)
cv2.imshow('mashiro',img)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
dst = np.zeros((height,width,1),np.uint8)
for i in range(0,height):
for j in range(0,width-1):
grayP0 = int(gray[i,j])
grayP1 = int(gray[i,j+1])
newP = grayP0-grayP1+150
if newP>255:
newP=255
elif newP<0:
newP=0
dst[i,j] = newP
cv2.imshow('mashiro1',dst)
cv2.waitKey(0)

22.颜色映射

import cv2
import numpy as np
img = cv2.imread('mashiro.jpg',1)
cv2.imshow('mashiro',img)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
dst = np.zeros((height,width,3),np.uint8)
for m in range(height):
for n in range(width):
 b,g,r = img[m,n]
b = b*1.5
g = g*1.3
if b >255:
b=255
if g>255:
g=255
dst[m,n] = b,g,r
cv2.imshow('mashiro1',dst)
cv2.waitKey(0)

23.油画特效

import cv2
import numpy as np
img = cv2.imread('mashiro.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
dst = np.zeros((height,width,3),np.uint8)
for i in range(4,height-4):
for j in range(4,width-4):
array1 = np.zeros(8,np.uint8)
for m in range(-4,4):
for n in range(-4,4):
p1=int(gray[i+m,j+n]/32)
array1[p1]=array1[p1]+1
currentMax = array1[0]
for k in range(0,8):
if currentMax
l=k
for m in range(-4,4):
for n in range(-4,4):
if gray[i+m,j+n]>(l*32) and gray[i+m,j+n]<((l+1)*32):
 b,g,r = img[m,n]
dst[i,j] = b,g,r
cv2.imshow('mashiro',dst)
cv2.waitKey(0)

# 程序算的会很慢很慢

24.线段绘制

import cv2

import numpy as np

img = cv2.imread('mashiro.jpg',1)

newImagInfo = (500,500,3)

dst = np.zeros(newImagInfo,np.uint8)

# 1.图片信息 2.开始位置 3.结束位置 4.颜色

cv2.line(dst,(100,100),(400,400),(0,0,255))

# 5.线条的宽度

cv2.line(dst,(100,200),(400,200),(0,255,255),20)

# 6.线条类型

cv2.line(dst,(100,300),(400,300),(0,255,0),20,cv2.LINE_AA)

# 绘制三角形，说白了就是三条线段

cv2.line(dst,(200,150),(50,250),(25,100,255))

# 第二条线段的起始位置是第一条线段的终止位置

cv2.line(dst,(50,250),(400,380),(25,100,255))

# 第三条线段的起始位置是第一条线段的起始位置，终止位置是第二条线段的终止位置

cv2.line(dst,(200,150),(400,380),(25,100,255))

cv2.imshow('mashiro',dst)

cv2.waitKey(0)

25.矩形圆形任意多边形绘制

import cv2

import numpy as np

newImgInfo = 500,500,3

dst = np.zeros(newImgInfo,np.uint8)

# 1.图片 2.左上角坐标 3.右下角坐标 4.颜色 5.是否填充(大于零：线条宽度，小于零：是否填充)

cv2.rectangle(dst,(50,100),(200,300),(255,0,0),-1)

# 1.图片 2.圆心 3.半径 4.颜色

cv2.circle(dst,(250,250),(50),(255,0,255),-1,cv2.LINE_AA)

# 椭圆 1.图片 2.椭圆圆心 3.长轴和短轴的长度 4.偏转角度 5.圆弧起始角度 6.圆弧终止角度 7.颜色 8.是否填充

cv2.ellipse(dst,(256,256),(150,100),0,0,180,(255,255,0),-1,cv2.LINE_AA)

# 定义任意角度

points = np.array([[150,50],[140,140],[200,170],[250,250],[150,50]],np.int32) # (5,2)

points = points.reshape((-1,1,2)) # (5,1,2)

cv2.polylines(dst,[points],True,(0,255,255))

cv2.imshow('mashiro',dst)

cv2.waitKey(0)

26.文字绘制

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
import numpy as np
img = cv2.imread('mashiro.jpg',1)
font = cv2.FONT_HERSHEY_COMPLEX

# 1.图片 2.文字的内容 3.写入的坐标 4.字体 5.字体大小 6.颜色 7，字体的粗细 8.线条类型

cv2.putText(img,'hello, i am mashiro····',(100,300),font,1,(200,100,255),2,cv2.LINE_AA)

cv2.imshow('mashiro',img)

cv2.waitKey(0)

27.图片绘制

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
img = cv2.imread('mashiro.jpg',1)
height = int(img.shape[0]*0.2)
width = int(img.shape[1]*0.2)
imgResize = cv2.resize(img,(width,height))
for i in range(height):
for j in range(width):
 img[i+200,j+350] = imgResize[i,j]
cv2.imshow('mashiro',img)
cv2.waitKey(0)

28.彩色图片直方图

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
import numpy as np
def ImageHist(img,e_type):
color = (255,255,255)
windowName = 'gray'
if e_type == 31:
color = (255,0,0)
windowName = 'b hist'
elif e_type == 32:
color = (0,255,0)
windowName = 'g hist'
elif e_type == 33:
color = (0,0,255)
windowName = 'r hist'

# 一定要用列表的形式 1.图片 2.计算直方图的通道 3.蒙版mask 4.直方图的size，多少种 5直方图中各个像素的值

hist = cv2.calcHist([img],[0],None,[256],[0.0,255.0])
minV,maxV,minV_indice,maxL_indice = cv2.minMaxLoc(hist)
histImg = np.zeros([256,256,3],np.uint8)
for h in range(256):
interNomal = int(hist[h]*256/maxV)
cv2.line(histImg,(h,256),(h,256-interNomal),color)
cv2.imshow(windowName,histImg)
return histImg
img = cv2.imread('mashiro.jpg',3)
channels = cv2.split(img) # RGB ---->R G B
for i in range(3):
ImageHist(channels[i],31+i)
cv2.waitKey(0)

29.灰度直方图均衡化

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
import numpy as np
img = cv2.imread('mashiro.jpg',1)
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
cv2.imshow('mashiro',gray)
dst = cv2.equalizeHist(gray)
cv2.imshow('mashiro1',dst)
cv2.waitKey(0)

30.彩色直方图均衡化

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
import numpy as np
img = cv2.imread('mashiro.jpg',3)
cv2.imshow('mashiro',img)
b,g,r = cv2.split(img) # split之后 得到三个通道的数据
bH = cv2.equalizeHist(b)
gH = cv2.equalizeHist(g)
rH = cv2.equalizeHist(r)
result = cv2.merge((bH,gH,rH)) # 将三个通道合成在一起
cv2.imshow('mashiro1',result)
cv2.waitKey(0)

31.YUV直方图均衡化

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
import numpy as np
img = cv2.imread('mashiro.jpg',1)
imgYUV = cv2.cvtColor(img,cv2.COLOR_BGR2YCrCb)
cv2.imshow('mashiro',img)
channelYUV = cv2.split(imgYUV)
channelYUV[0] = cv2.equalizeHist(channelYUV[0])
channels = cv2.merge(channelYUV)
result = cv2.cvtColor(channels,cv2.COLOR_YCrCb2BGR)
cv2.imshow('mashiro1',result)
cv2.waitKey(0)

32.图片修补

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
import numpy as np
img = cv2.imread('mashiro.jpg',1)
for i in range(200,300):
 img[i,200] = (255,255,255)
 img[i,200+1] = (255,255,255)
 img[i,200-1] = (255,255,255)
for i in range(150,250):
 img[250,i] = (255,255,255)
 img[250+1,i] = (255,255,255)
 img[250-1,i] = (255,255,255)
cv2.imwrite('damaged_mashiro.jpg',img)
img = cv2.imread('damaged_mashiro.jpg',3)
cv2.imshow('damaged_mashiro.jpg',img)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
paint = np.zeros((height,width,1),np.uint8)
for i in range(200,300):
paint[i,200] = 255
paint[i,200+1] = 255
paint[i,200-1] = 255
for i in range(150,250):
paint[250,i] = 255,
paint[250+1,i] = 255
paint[250-1,i] = 255
cv2.imshow('paint',paint)
imgDst = cv2.inpaint(img,paint,3,cv2.INPAINT_TELEA)
cv2.imshow('mashiro',imgDst)
cv2.waitKey(0)

33.亮度增强

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
import numpy as np
img = cv2.imread('mashiro.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
dst = np.zeros((height,width,3),np.uint8)

# 新图片像素的亮度等于原图片像素的亮度加上一个固定值

cv2.imshow('mashiro',img)
for i in range(height):
for j in range(width):
 (b,g,r) = img[i,j]
bb = int(b)+120 # 自由变换
gg = int(g)+120
rr = int(r)+120
if bb > 255:
bb = 255
if gg > 255:
gg = 255
if rr > 255:
rr = 255
 dst[i,j] = img[i,j]
cv2.imshow('mashiro1',dst)
cv2.waitKey(0)

34.磨皮美白

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
# 原理：双边滤波
import cv2
img = cv2.imread('mashiro.jpg',1)
cv2.imshow('mashiro',img)
dst = cv2.bilateralFilter(img,15,35,35)
cv2.imshow('mashiro1',dst)
cv2.waitKey(0)

# 由于是动漫图片，然鹅并看不出什么效果

35.高斯滤波

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
img = cv2.imread('mashiro.jpg',1)
cv2.imshow('mashiro',img)
dst = cv2.GaussianBlur(img,(5,5),1.5)
cv2.imshow('mashiro1',dst)
cv2.waitKey(0)

# 如果原图上有许多的小点点，那么高斯滤波可以过滤掉，同时图片也会变得模糊

36.均值滤波

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
import numpy as np
img = cv2.imread('mashiro.jpg',1)
cv2.imshow('mashiro',img)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
dst = np.zeros((height,width,3),np.uint8)
for i in range(3,height-3):
for j in range(3,width-3):
sum_b = int(0)
sum_g = int(0)
sum_r = int(0)
for m in range(-3,3):
for n in range(-3,3):
 b,g,r = img[i+m,j+n]
sum_b = sum_b + int(b)
sum_g = sum_g + int(g)
sum_r = sum_r + int(r)
b = np.uint8(sum_b/36)
g = np.uint8(sum_g/36)
r = np.uint8(sum_r/36)
dst[i,j] = b,g,r
cv2.imshow('mashiro1',dst)
cv2.waitKey(0)

# 然而并无卵用，程序还很慢

37.中值滤波

#!/usr/bin/env python
# -*- coding:utf-8 -*-
# author:love_cat
import cv2
import numpy as np
img = cv2.imread('mashiro.jpg', 1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
cv2.imshow('mashiro', img)
dst = np.zeros((height, width, 3), np.uint8)
collect = np.zeros(9, np.uint8)
for i in range(1, height-1):
for j in range(1, width-1):
k = 0
for m in range(-1, 2):
for n in range(-1, 2):
 gray = img[i + m, j + n]
collect[k] = gray
k = k + 1
for k in range(0, 9):
p1 = collect[k]
for t in range(k + 1, 9):
if p1 < collect[t]:
mid = collect[t]
collect[t] = p1
p1 = mid
dst[i, j] = collect[4]
cv2.imshow('mashiro1',dst)
cv2.waitKey(0)

# 效果并不理想,程序也很慢

38.视频分解成图片

# 视频分解图片

# 1 load 2 info 3 parse 4 imshow imwrite

import cv2

# 打开一个视频获取，一个句柄

cap = cv2.VideoCapture(r"01.mp4")

# 判断是否打开

isOpened = cap.isOpened

print(isOpened)

# 获取视频的帧率

fps = cap.get(cv2.CAP_PROP_FPS)

# 获取图片的宽度和高度

width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))

height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))

print("帧率=%s，宽度=%s,高度=%s" % (fps, width, height))

i = 0

while isOpened:

if i == 100:

break # 我们只获取100张图片

else:

i += 1

# 读取每一张flag，frame

# flag表示是否读取成功

# frame表示图片的内容

(flag, frame) = cap.read()

fileName = "image"+str(i)+".jpg"

print(fileName)

if flag:

cv2.imwrite(fileName, frame, [cv2.IMWRITE_JPEG_QUALITY, 100]) # 表示精度最高

print("end!!!")

# 程序运行结果

'''

帧率=15.0，宽度=1280,高度=720

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end!!!

'''