1> 颜色反转
# 0-255 255-当前
import cv2
import numpy as np
img = cv2.imread('2.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) # 1 代表一个像素是由几个颜色组成的
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 反转
# RGB 255-R=newR
import cv2
import numpy as np
img = cv2.imread('2.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
dst = np.zeros((height,width,3),np.uint8) # 3 代表一个像素是由几个颜色组成的
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)
最终效果图
效果图.png
2> 马赛克
import cv2
import numpy as np
img = cv2.imread('2.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
for m in range(100,300):
for n in range(50,200):
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('dst',img)
cv2.waitKey(0)
最终效果图（有点邪恶~）
效果图.png
3> 图片融合
# dst = src1*a + src2*(1-a)
import cv2
import numpy as np
img0 = cv2.imread('2.jpg',1)
img1 = cv2.imread('3.jpg',1)
imgInfo = img0.shape
height = imgInfo[0]
width = imgInfo[1]
roiH = int(height/2)
roiW = int(width/2)
img0ROI = img0[0:roiH,0:roiW]
img1ROI = img1[0:roiH,0:roiW]
dst = np.zeros((roiH,roiW,3),np.uint8)
dst = cv2.addWeighted(img0ROI,0.5,img1ROI,0.5,0)
cv2.imshow('dst',dst)
cv2.waitKey(0)
最终效果图
效果图.png
4> 边缘检测
import cv2
import numpy as np
import random
img = cv2.imread('2.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)
cv2.imshow('dst',dst)
cv2.waitKey(0)
效果图
image.png
5> 浮雕效果
import cv2
import numpy as np
import random
img = cv2.imread('2.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
# newP = gray0 - gray1 + 150
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
if newP < 0:
newP = 0
dst[i,j] = newP
cv2.imshow('dst',dst)
cv2.waitKey(0)
最终效果图
效果图.png