python中opencv是什么_python-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)

copycode.gif

1229382-20180516002528393-1109764650.png

2. 图片写入

copycode.gif

#!/usr/bin/env python

# -*- coding:utf-8 -*-

# author:love_cat

import cv2

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

cv2.imwrite('mashiro1.jpg',img)

copycode.gif

3.不同图片质量保存

copycode.gif

#!/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

copycode.gif

4.像素操作基础

copycode.gif

#!/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)

copycode.gif

1229382-20180516002926491-229897311.png

5.图片缩放

copycode.gif

#!/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)

copycode.gif

1229382-20180516003038351-475109920.png

6.图片缩放（源码实现）

copycode.gif

#!/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)

copycode.gif

7.图片剪切

copycode.gif

#!/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)

copycode.gif

1229382-20180516003301212-1506066048.png

8.图片移位

copycode.gif

#!/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)

copycode.gif

1229382-20180516003348129-1942194599.png

9.图片移位（源码实现）

copycode.gif

#!/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)

copycode.gif

10.图片镜像

copycode.gif

#!/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)

copycode.gif

1229382-20180516003513940-473980736.png

11.图片仿射变换

copycode.gif

#!/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)

copycode.gif

1229382-20180516003618302-564325183.png

12.图片旋转

copycode.gif

#!/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)

copycode.gif

1229382-20180516003655088-2126333148.png

13.闲的蛋疼（批量将图片进行上述操作）

copycode.gif

#!/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)

copycode.gif

14.灰度处理

copycode.gif

#!/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)

copycode.gif

1229382-20180516004017379-967034486.png

15.颜色反转

copycode.gif

#!/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)

copycode.gif

1229382-20180516004148060-1275928837.png

1229382-20180516004125327-989403274.png

16.马赛克

copycode.gif

#!/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)

copycode.gif

1229382-20180516004226525-1813911357.png

17.毛玻璃

copycode.gif

#!/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)

copycode.gif

1229382-20180516004307451-335150380.png

18.真白18岁生日快乐

19.图片融合

copycode.gif

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

copycode.gif

1229382-20180516004407016-1753639708.png

20.边缘检测

copycode.gif

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)

copycode.gif

1229382-20180516004445637-255514107.png

21.浮雕效果

copycode.gif

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)

copycode.gif

1229382-20180516004526996-995268397.png

22.颜色映射

copycode.gif

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)

copycode.gif

1229382-20180516004604470-2111127942.png

23.油画特效

copycode.gif

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

copycode.gif

1229382-20180516004645534-1863837143.png

24.线段绘制

copycode.gif

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)

copycode.gif

1229382-20180516004718974-1311875951.png

25.矩形圆形任意多边形绘制

copycode.gif

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)

copycode.gif

1229382-20180516004821100-1214876246.png

26.文字绘制

copycode.gif

#!/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)

copycode.gif

1229382-20180516004938593-1133848221.png

27.图片绘制

copycode.gif

#!/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)

copycode.gif

1229382-20180516005023699-677773526.png

28.彩色图片直方图

copycode.gif

#!/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)

copycode.gif

1229382-20180516005057471-1283057062.png

29.灰度直方图均衡化

copycode.gif

#!/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)

copycode.gif

1229382-20180516005134009-1177753774.png

30.彩色直方图均衡化

copycode.gif

#!/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)

copycode.gif

1229382-20180516005210606-1587679815.png

31.YUV直方图均衡化

copycode.gif

#!/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)

copycode.gif

1229382-20180516005251773-1717073847.png

32.图片修补

copycode.gif

#!/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)

copycode.gif

1229382-20180516005321956-234980789.png

33.亮度增强

copycode.gif

#!/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)

copycode.gif

1229382-20180516005352907-1982456861.png

34.磨皮美白

copycode.gif

#!/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

copycode.gif

1229382-20180516005428565-1254574967.png

35.高斯滤波

copycode.gif

#!/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

copycode.gif

1229382-20180516005500692-1933760109.png

36.均值滤波

copycode.gif

#!/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

copycode.gif

1229382-20180516005537035-567840293.png

37.中值滤波

copycode.gif

#!/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

copycode.gif

1229382-20180516005610810-1138547707.png

38.视频分解成图片

copycode.gif

# 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

image1.jpg

image2.jpg

image3.jpg

image4.jpg

image5.jpg

image6.jpg

image7.jpg

image8.jpg

image9.jpg

image10.jpg

image11.jpg

image12.jpg

image13.jpg

image14.jpg

image15.jpg

image16.jpg

image17.jpg

image18.jpg

image19.jpg

image20.jpg

image21.jpg

image22.jpg

image23.jpg

image24.jpg

image25.jpg

image26.jpg

image27.jpg

image28.jpg

image29.jpg

image30.jpg

image31.jpg

image32.jpg

image33.jpg

image34.jpg

image35.jpg

image36.jpg

image37.jpg

image38.jpg

image39.jpg

image40.jpg

image41.jpg

image42.jpg

image43.jpg

image44.jpg

image45.jpg

image46.jpg

image47.jpg

image48.jpg

image49.jpg

image50.jpg

image51.jpg

image52.jpg

image53.jpg

image54.jpg

image55.jpg

image56.jpg

image57.jpg

image58.jpg

image59.jpg

image60.jpg

image61.jpg

image62.jpg

image63.jpg

image64.jpg

image65.jpg

image66.jpg

image67.jpg

image68.jpg

image69.jpg

image70.jpg

image71.jpg

image72.jpg

image73.jpg

image74.jpg

image75.jpg

image76.jpg

image77.jpg

image78.jpg

image79.jpg

image80.jpg

image81.jpg

image82.jpg

image83.jpg

image84.jpg

image85.jpg

image86.jpg

image87.jpg

image88.jpg

image89.jpg

image90.jpg

image91.jpg

image92.jpg

image93.jpg

image94.jpg

image95.jpg

image96.jpg

image97.jpg

image98.jpg

image99.jpg

image100.jpg

end!!!

'''

转自：https://www.cnblogs.com/traditional/p/9043931.html

copycode.gif

本文来自互联网用户投稿，该文观点仅代表作者本人，不代表本站立场。本站仅提供信息存储空间服务，不拥有所有权，不承担相关法律责任。如若转载，请注明出处：http://www.mzph.cn/news/455643.shtml

如若内容造成侵权/违法违规/事实不符，请联系多彩编程网进行投诉反馈email:809451989@qq.com，一经查实，立即删除！

相关文章

【Tensorflow】卷积神经网络实现艺术风格化通过Vgg16实现

【Tensorflow】卷积神经网络实现艺术风格化通过Vgg16实现

卷积神经网络实现艺术风格化 基于卷积神经网络实现图片风格的迁移&#xff0c;可以用于大学生毕业设计基于python&#xff0c;深度学习&#xff0c;tensorflow卷积神经网络&#xff0c; 通过Vgg16实现&#xff0c;一幅图片内容特征的基础上添加另一幅图片的风格特征从而生成一幅…
阅读更多...
抗误码技术

抗误码技术

抗误码技术&#xff1a; 视频传输过程中的错误是不可避免的&#xff0c;抗误码技术历来都足视频领域一个研究的热点。H264标准继承r以前视频编码标准中某些优秀的错误恢复工具&#xff0c;同时也改进和创新了多种错误恢复丁具。这些错误恢复的工具主要有&#xff1a;参数集、数…
阅读更多...
Linux统计文件行数、字数、字节数

Linux统计文件行数、字数、字节数

2019独角兽企业重金招聘Python工程师标准>>> 语法&#xff1a;wc [选项] 文件 说明&#xff1a;该命令统计给定文件中的字节数、字数、行数。如果没有给出文件名&#xff0c;则从标准输入读取。wc同时也给出所有指定文件的总统计数。字是由空格字符区分开的最大字符…
阅读更多...
【Tensorflow】人脸128个关键点识别基于卷积神经网络实现

【Tensorflow】人脸128个关键点识别基于卷积神经网络实现

引言&#xff1a; 卷积神经网络 卷积神经网络最早是为了解决图像识别的问题,现在也用在时间序列数据和文本数据处理当中,卷积神经网络对于数据特征的提取不用额外进行,在对网络的训练的过程当中,网络会自动提取主要的特征.卷积神经网络直接用原始图像的全部像素作为输入,但是内…
阅读更多...
python 爬虫 包_python爬虫学习之路-抓包分析

python 爬虫 包_python爬虫学习之路-抓包分析

利用浏览器抓包&#xff0c;是爬虫中的很实用的技能。在爬虫编程之前&#xff0c;我们要对抓取的目标页面有所了解&#xff0c;比如浏览器的这个请求这个页面中间都经历了什么&#xff0c;数据是怎么发送和返回的。 抓包的作用 我把抓包分析的作用简单列一下&#xff1a; 分析请…
阅读更多...
帧间EC原理和过程

帧间EC原理和过程

出错的宏块&#xff08;图中灰色表示&#xff09;根据上、下、左、右四个方向相邻宏块的不同分割情况及预测类型进行插值。将最后的结果中进行比较&#xff0c;选取边界像素差值之和最小者为最优的EC方案。其步骤为&#xff1a; 1、判断相邻宏块左上角8*8块的预测模式是否大于R…
阅读更多...
Maven依赖的是本地工程还是仓库jar包？

Maven依赖的是本地工程还是仓库jar包？

相信大家都碰见过maven配置的依赖或者是jar包或者是工程&#xff0c;在开发的过程当中&#xff0c;我们当然需要引入的是工程&#xff0c;这样查看maven依赖的文件的时候&#xff0c;就能直接查看到源码。 一、本地工程依赖 举个例子&#xff0c;其架构如下所示&#xff08;以下…
阅读更多...
关于django新版本无法使用MySQL数据库的问题

关于django新版本无法使用MySQL数据库的问题

关于django新版本无法使用MySQL数据库的问题 参考这里 稍微记录下Django2.2使用MariaDB和MySQL遇到的坑 现在演示一下整个流程吧 1.创建项目和应用 PS&#xff1a;你也可以使用PyCharm直接创建项目 2.注册应用 先把刚刚创建的应用添加进去 3.配置MySQL或者MariaDB 4.PyMySQL替…
阅读更多...
python连接sql数据库_python连接sql server数据库实现增删改查

python连接sql数据库_python连接sql server数据库实现增删改查

简述 python连接微软的sql server数据库用的第三方模块叫做pymssql&#xff08;document&#xff1a;http://www.pymssql.org/en/stable/index.html&#xff09;。在官方文档可以看到&#xff0c;pymssql是基于_mssql模块做的封装&#xff0c;是为了遵守python的DBAPI规范接口.…
阅读更多...
es5.0 安装head插件

es5.0 安装head插件

es5.0的安装和之前的版本有些区别,我的电脑用plugin install 没成功, 查了一下资料,说是可以用grunt进行安装,启动; 1,先安装grunt: grunt是一个很方便的构建工具&#xff0c;可以进行打包压缩、测试、执行等等的工作&#xff0c;5.0里的head插件就是通过grunt启动的。 npm ins…
阅读更多...
套接字 资料查阅

套接字 资料查阅

(3)套接字(socket) 一个完整的网络应用程序包括客户端和服务器两个部分。网间通信进程需要由两个进程组成&#xff0c;并且只能用同一种协议。也就是说&#xff0c;不能在通信的一端使用TCP协议&#xff0c;而另一端则用UDP协议。一个完整的网络通信需要一个五元组来标识…
阅读更多...
linux mysql安装_Linux下安装mysql服务（超详细）

linux mysql安装_Linux下安装mysql服务（超详细）

Mysql数据库的安装对于开发者来说&#xff0c;是我们必然会面对的问题&#xff0c;它的安装过程其实并不复杂&#xff0c;并且网络上的安装教程也非常多&#xff0c;但是对于新手来说&#xff0c;各种不同形式的安装教程&#xff0c;又给新手们带来了要选择哪种方式进行安装的难…
阅读更多...
day2 操作系统

day2 操作系统

一.为何要有操作系统 程序员无法把所有的硬件操作细节都了解到&#xff0c;管理这些硬件并且加以优化使用是非常繁琐的工作&#xff0c;这个繁琐的工作就是操作系统来干的&#xff0c;有了他&#xff0c;程序员就从这些繁琐的工作中解脱了出来&#xff0c;只需要考虑自己的应用…
阅读更多...
python安装不了jupyter_python学习笔记——Windowns下Python3之安装jupyter

python安装不了jupyter_python学习笔记——Windowns下Python3之安装jupyter

Windowns下Python3之安装jupyter Jupyter notebook&#xff1a; 一个交互式笔记本&#xff0c;支持运行40多种编程语言。 利用它来写Python&#xff0c;代码和运行结果都可以保存下载&#xff0c;十分方便。本文主要以自身的安装过程为例&#xff0c;结合遇到的问题&#xff0c…
阅读更多...
matlab 三维核密度图_Matlab精彩画图示例：三维网状图和三维曲面图

matlab 三维核密度图_Matlab精彩画图示例：三维网状图和三维曲面图

接上篇&#xff1a;Matlab精彩画图示例&#xff1a;绘制图上图这篇介绍两个绘制三维图的命令&#xff1a;mesh - 绘制三维网状图surf - 绘制三维曲面图matlab代码如下&#xff1a;绘制三维图的matlab代码示例程序运行结果如下&#xff1a;mesh(X,Y,Z) draws a wireframe mesh w…
阅读更多...
JDBC1

JDBC1

1.jdbc的概述 是sun公司统一提供的一套接口规范,各个数据库生产商提供实现 注册驱动,获得连接,获得执行的SQL语句对象,释放资源 package com.learn.jdbc;import java.sql.Connection; import java.sql.DriverManager; import java.sql.SQLException;import org.junit.Test;publ…
阅读更多...
python程序怎么保存到u盘_python实现usb自动拷贝程序的方法

python程序怎么保存到u盘_python实现usb自动拷贝程序的方法

python实现usb自动拷贝程序的方法 发布时间&#xff1a;2020-06-28 09:07:05 来源&#xff1a;亿速云 阅读&#xff1a;135 作者&#xff1a;清晨 这篇文章将为大家详细讲解有关python实现usb自动拷贝程序的方法&#xff0c;小编觉得挺实用的&#xff0c;因此分享给大家做个参考…
阅读更多...
young people can also be a leader

young people can also be a leader

2019独角兽企业重金招聘Python工程师标准>>> The leaders or directors of organizations are often older people. But some people say that young people can also be a leader. To what extent do you agree or disagree? In my view , young people can also …
阅读更多...
BZOJ 2004 公交线路(状压DP+矩阵快速幂)

BZOJ 2004 公交线路(状压DP+矩阵快速幂)

注意到每个路线相邻车站的距离不超过K&#xff0c;也就是说我们可以对连续K个车站的状态进行状压。 然后状压DP一下&#xff0c;用矩阵快速幂加速运算即可。 #include <stdio.h> #include <stdlib.h> #include <string.h> #include <algorithm>#define…
阅读更多...
python爬取网易云歌单_详解python selenium 爬取网易云音乐歌单名

python爬取网易云歌单_详解python selenium 爬取网易云音乐歌单名

目标网站&#xff1a;首先获取第一页的数据&#xff0c;这里关键要切换到iframe里打印一下获取剩下的页数&#xff0c;这里在点击下一页之前需要设置一个延迟&#xff0c;不然会报错。结果&#xff1a;一共37页&#xff0c;爬取完毕后关闭浏览器 完整代码&#xff1a; url htt…
阅读更多...
推荐文章
最新文章

Copyright @ 2022~2023