python+opencv+图像特效（图像灰度处理、颜色翻转、图片融合，边缘检测，浮雕效果，颜色映射） - 好文

原图

图像灰度处理
#方式1 import cv2 #读取彩色原图 img0=cv2.imread('E:/python_cv/01.jpg',1) #读取灰度图
img1=cv2.imread('E:/python_cv/01.jpg',0) print(img0.shape) print(img1.shape)
cv2.imshow('gary',img1) cv2.waitKey(0)#方式2 import cv2 #读取彩色原图
src=cv2.imread('E:/python_cv/01.jpg',1)
dst=cv2.cvtColor(src,cv2.COLOR_BGR2GRAY) cv2.imshow('gary',dst) cv2.waitKey(0)
#方式3 import cv2 import numpy as np img=cv2.imread('E:/python_cv/01.jpg',1)
img_info=img.shape image_height=img_info[0] image_weight=img_info[1]
dst=np.zeros((image_height,image_weight,3),np.uint8) #当彩色图像三个通道的值都相同时，即为灰度图像
for i in range(image_height): for j in range(image_weight): (b,g,r)=img[i][j]
gray=(int(b)+int(g)+int(r))/3 #防止越界，转换类型 dst[i,j]=np.uint8(gray)
cv2.imshow('gary',dst) cv2.waitKey(0)#方式4 import cv2 import numpy as np
img=cv2.imread('E:/python_cv/01.jpg',1) img_info=img.shape
image_height=img_info[0] image_weight=img_info[1]
dst=np.zeros((image_height,image_weight,3),np.uint8) #当彩色图像三个通道的值都相同时，即为灰度图像
for i in range(image_height): for j in range(image_weight): (b,g,r)=img[i][j]
gray=0.299*int(b)+0.587*int(g)+0.114*int(r) dst[i,j]=np.uint8(gray)
cv2.imshow('gary',dst) cv2.waitKey(0)
灰度处理很重要，也是图像处理中的基础操作，在实际运用中要求实时性，涉及优化，比如：

* 定点操作比浮点操作要快
* +-比*/快，移位比*/快import cv2 import numpy as np
img=cv2.imread('E:/python_cv/01.jpg',1) img_info=img.shape
image_height=img_info[0] image_weight=img_info[1]
dst=np.zeros((image_height,image_weight,3),np.uint8) #当彩色图像三个通道的值都相同时，即为灰度图像
for i in range(image_height): for j in range(image_weight): (b,g,r)=img[i][j] #
gray=0.299*int(b)+0.587*int(g)+0.114*int(r) #优化 b=int(b) g=int(g) r=int(r) #
gray=(b+2*g+r)/4 gray=(b+(g<<1)+r)>>2 dst[i,j]=np.uint8(gray)
cv2.imshow('gary',dst) cv2.waitKey(0)
颜色翻转
灰度图像素值为0到255，若当前的像素值为i,翻转过后为255-iimport cv2 import numpy as np #读取彩色原图
src=cv2.imread('E:/python_cv/01.jpg',1)
gray=cv2.cvtColor(src,cv2.COLOR_BGR2GRAY) img_info=src.shape
image_height=img_info[0] image_weight=img_info[1]
dst=np.zeros((image_height,image_weight,1),np.uint8) for i in
range(image_height): for j in range(image_weight): grayPixel=gray[i][j]
dst[i][j]=255-grayPixel cv2.imshow('gary',dst) cv2.waitKey(0)
原灰度图反转灰度图

彩色图反转
import cv2 import numpy as np #读取彩色原图 src=cv2.imread('E:/python_cv/01.jpg',1)
img_info=src.shape image_height=img_info[0] image_weight=img_info[1]
dst=np.zeros((image_height,image_weight,3),np.uint8) for i in
range(image_height): for j in range(image_weight): (b,g,r)=src[i][j]
dst[i][j]=(255-b,255-g,255-r) cv2.imshow('src',src) cv2.imshow('dst',dst)
cv2.waitKey(0)
彩色图反转图

图片融合
import cv2 import numpy as np #读取彩色原图 src=cv2.imread('E:/python_cv/01.jpg',1)
src1=cv2.imread('E:/python_cv/02.jpg',1) img_info=src.shape
image_height=img_info[0] image_weight=img_info[1] roi_h=int(image_height/2)
roi_w=int(image_weight/2) src_roi=src[0:roi_h,0:roi_w]
src1_roi=src1[0:roi_h,0:roi_w] dst=np.zeros((roi_h,roi_w,3),np.uint8)
dst=cv2.addWeighted(src_roi,0.5,src1_roi,0.5,0) cv2.imshow('dst',dst)
cv2.waitKey(0)
canny 边缘检测

步骤：灰度图，高斯滤波，canny
import cv2 import numpy as np gray=cv2.imread('E:/python_cv/01.jpg',0)
img=cv2.GaussianBlur(gray,(3,3),0) dst=cv2.Canny(img,50,50)
cv2.imshow('gray',gray) cv2.imshow('gauss',img) cv2.imshow('dst',dst)
cv2.waitKey(0)
灰度图高斯滤波canny

soble边缘检测
import cv2 import numpy as np import math
gray=cv2.imread('E:/python_cv/01.jpg',0) imgInfo=gray.shape height=imgInfo[0]
weight=imgInfo[1] cv2.imshow('src',gray)
dst=np.zeros((height,weight,1),np.uint8) ''' sobel 1.算子模板 2.图像卷积 3.阈值判决竖直模板
水平模板 [1 2 1 [1 0 -1 0 0 0 2 0 -2 -1-2-1] 1 0 -1] ''' for i in
range(0,height-2): for j in range(0,weight-2):
gy=gray[i,j]*1+gray[i,j+1]*2+gray[i,j+2]*1-gray[i+2,j]-2*gray[i+2,j+1]-gray[i+2,j+2]*1
gx=gray[i,j]*1-gray[i,j+2]+gray[i+1,j]*2-2*gray[i+1,j+2]+gray[i+2,j]-gray[i+2,j+2]
grad=math.sqrt(gx*gx+gy*gy) if grad>50: dst[i,j]=255 else: dst[i,j]=0
cv2.imshow('dst',dst) cv2.waitKey(0)
原图sobel
import cv2 import numpy as np gray=cv2.imread('E:/python_cv/01.jpg',0)
imgInfo=gray.shape height=imgInfo[0] weight=imgInfo[1] #浮雕效果
dst=np.zeros((height,weight,1),np.uint8) for i in range(0,height): for j in
range(0,weight-1): gray0=gray[i,j] gray1=gray[i,j+1] newp=gray0-gray1+150 if
newp>255: newp=255 else: newp=0 dst[i,j]=newp cv2.imshow('dst',dst)
cv2.waitKey(0)
原图浮雕效果

风格转换
import cv2 import numpy as np img=cv2.imread('E:/python_cv/01.jpg',1)
imgInfo=img.shape height=imgInfo[0] weight=imgInfo[1] cv2.imshow('src',img) '''
颜色风格，rgb-->RGB b=b*1.5 g=g*1.3 ''' dst=np.zeros((height,weight,3),np.uint8) for
i in range(0,height): for j in range(0,weight): (b,g,r)=img[i,j] b=1.5*b
g=1.3*g if b>255: b=255 if g>255: g=255 dst[i,j]=(b,g,r) cv2.imshow('dst',dst)
cv2.waitKey(0)
原图颜色风格

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