opencv 图片特效

opencv 图片特效

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图片颜色反转

灰度图片颜色反转

#0-255 255-当前 import cv2 import numpy as np img = cv2.imread('image0.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):         grayPixel = gray[i,j]         dst[i,j] = 255-grayPixel cv2.imshow('dst',dst) cv2.waitKey(0)

彩色图片颜色反转

#RGB 255-R=newR #0-255 255-当前 import cv2 import numpy as np img = cv2.imread('image0.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]         dst[i,j] = (255-b,255-g,255-r) cv2.imshow('dst',dst) cv2.waitKey(0)

马赛克

import cv2 import numpy as np img = cv2.imread('image0.jpg',1) imgInfo = img.shape height = imgInfo[0] width = imgInfo[1] for m in range(100,300):     for n in range(100,200):         # pixel ->10*10         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('dst',img) cv2.waitKey(0)

毛玻璃

import cv2 import numpy as np import random img = cv2.imread('image0.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)#0-8         (b,g,r) = img[m+index,n+index]         dst[m,n] = (b,g,r) cv2.imshow('dst',dst) cv2.waitKey(0)

图片融合

dst = src1*a+src2*(1-a)

# dst  = src1*a+src2*(1-a) import cv2 import numpy as np img0 = cv2.imread('image0.jpg',1) img1 = cv2.imread('image1.jpg',1) imgInfo = img0.shape height = imgInfo[0] width = imgInfo[1] # ROI roiH = int(height/2) roiW = int(width/2) img0ROI = img0[0:roiH,0:roiW] img1ROI = img1[0:roiH,0:roiW] # dst dst = np.zeros((roiH,roiW,3),np.uint8) dst = cv2.addWeighted(img0ROI,0.5,img1ROI,0.5,0)#add src1*a+src2*(1-a) # 1 src1 2 a 3 src2 4 1-a cv2.imshow('dst',dst) cv2.waitKey(0)

边缘检测

import cv2 import numpy as np import random img = cv2.imread('3.jpg',1) imgInfo = img.shape height = imgInfo[0] width = imgInfo[1] cv2.imshow('src',img) #canny 1 gray 2 高斯 3 canny gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) imgG = cv2.GaussianBlur(gray,(3,3),0) dst = cv2.Canny(img,50,50) #图片卷积――》th cv2.imshow('dst',dst) cv2.waitKey(0)

文章来源: opencv 图片特效