OpenCV+python计算机视觉图像处理2——图片特效&绘制线段文字

灰度处理

#方法一 imread
import cv2
img0 = cv2.imread('image0.jpg',0)
img1 = cv2.imread('image0.jpg',1)
print(img0.shape)
print(img1.shape)
cv2.imshow('src',img0)
cv2.waitKey(0)

#方法二 cvtColor
import cv2
img = cv2.imread('image0.jpg',1)
dst = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) #颜色空间转换 1.data 2.BGR gray
cv2.imshow('src',dst)
cv2.waitKey(0)

#方法三 （R+G+B）/3
import cv2
import numpy as np
img = cv2.imread('image0.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]

#RGB R=G=B = gray （R+G+B）/3
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)
cv2.imshow('dst',dst)
cv2.waitKey(0)

#方法四 gray = r*0.299+g*0.587+b*0.114
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]
        b = int(b)
        g = int(g)
        r = int(r)
        gray = r*0.299+g*0.587+b*0.114
        dst[i,j] = np.uint8(gray)
cv2.imshow('dst',dst)
cv2.waitKey(0)

算法优化

#原则：定点运算>浮点运算  +-、移位 > */ 
#方法四 gray = r*0.299+g*0.587+b*0.114
# *4 *100 *1000 *10000
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]
        b = int(b)
        g = int(g)
        r = int(r)
        #gray = (r*1+g*2+b*1)/4
        gray = (r+(g<<1)+b)>>2
        dst[i,j] = np.uint8(gray)
cv2.imshow('dst',dst)
cv2.waitKey(0)

颜色反转

灰度图像颜色反转

#0-255 255-当前像素
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,3),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)

彩色图像颜色反转

#RGB 255-R=newR
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]
# 遍历马赛克矩形范围内所有像素点  选中一个像素替换10*10中的所有像素点
#每隔十个像素点取一个像素值
for m in range(100,300):
    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('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   #随机范围选取一个数
for i in range(0,height-mm):
    for j in range(0,width-mm):
        index = int(random.random()*8)  #随机数
        (b,g,r) = img[i+index,j+index]
        dst[i,j] = (b,g,r) 
cv2.imshow('dst',dst)
cv2.waitKey(0)

图片融合

# 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 = img.shape
height = imgInfo[0]
width = imgInfo[1]
#感兴趣范围 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((height,width,3),np.uint8)
dst = cv2.addWeighted(img0ROI,0.5,img1ROI,0.5,0)  # src1*a+src2*(1-a)
cv2.imshow('dst',dst)
cv2.waitKey(0)

边缘检测

canny 1.gray 2.高斯 3.canny

import cv2
import numpy as np
img = cv2.imread('image0.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
cv2.imshow('src',img)

gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
imgG = cv2.GaussianBlur(gray,(3,3),0)
dst = cv2.Canny(img,50,50)   #1.data 2.门限th 图片卷积>th
cv2.imshow('dst',dst)
cv2.waitKey(0)

源码形式：

import cv2
import numpy as np
import math
img = cv2.imread('image0.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
cv2.imshow('src',img)

#sobel 1.算子模板 2.图片卷积 3.阈值判决
#[1 2 1       [1 0 -1
# 0 0 0        2 0 -2
#-1 -2 -1]     1 0 -1]

#[1 2 3 4] [a b c d]   a*1+b*2+c*3+d*4 = dst
# sqrt(a*a+b*b) = f > th
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
dst = np.zeros((height,width,1),np.uint8)
for i in range(0,height-2):
    for j in range(0,width-2):
        gy = gray[i,j]*1+gray[i,j+1]*2+gray[i,j+2]*1-gray[i+2,j]*1-gray[i+2,j+1]*2-gray[i+2,j+2]*1
        gx = gray[i,j]*1+gray[i+1,j]*2+gray[i+2,j]*1-gray[i,j+2]*1-gray[i+1,j+2]*2-gray[i+2,j+2]*1
        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)

浮雕效果

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)
# 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)

颜色映射

import cv2
import numpy as np
img = cv2.imread('image0.jpg',1)
cv2.imshow('src',img)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
#rgb -> RGB new “蓝色”
#b = b*1.5
#g = g*1.3
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 = b*1.5
        g = g*1.3
        if b>255:
            b = 255
        if g>255:
            g = 255
        dst[i,j] = (b,g,r)
cv2.imshow('dst',dst)
cv2.waitKey(0)

油画特效

# 1.rgb->gray 
#2.将abs图像分割成若干个小方块 7*7 10*10 
#3. 将这些方块中的像素，映射到相应的灰度等级
#（划分灰度值等级 0-255 256 4段 64个灰度等级 0-36 64-127）
#4.灰度段中像素的个数统计 count
#5.用统计的平均值代替原来的像素值
import cv2
import numpy as np
img = cv2.imread('image00.jpg',1)
cv2.imshow('src',img)
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]
        l = 0
        for k in range(0,8):
            if currentMax<array1[k]:
                currentMax = array1[k]
                l = k    
        #简化 均值
        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[i+m,j+n]
        dst[i,j] = (b,g,r)
cv2.imshow('dst',dst)
cv2.waitKey(0)               

线段绘制

import cv2
import numpy as np
newImageInfo = (500,500,3)
dst = np.zeros(newImageInfo,np.uint8)
# line
#1.dst 2.begin 3.end 4.color 5.line width 6.line type
cv2.line(dst,(100,100),(400,400),(0,0,255))
cv2.line(dst,(100,200),(400,200),(0,255,255),20)
cv2.line(dst,(100,300),(400,300),(0,255,0),20,cv2.LINE_AA)

cv2.line(dst,(200,150),(50,250),(25,100,255))
cv2.line(dst,(50,250),(400,380),(25,100,255))
cv2.line(dst,(400,380),(200,150),(25,100,255))

cv2.imshow('dst',dst)
cv2.waitKey(0)

矩形圆形任意多边形绘制

import cv2
import numpy as np
newImageInfo = (500,500,3)
dst = np.zeros(newImageInfo,np.uint8)

#1.dst 2.左上角 3.右下角 4.颜色 5.是否fill -1 >0 line width
cv2.rectangle(dst,(50,100),(200,300),(255,0,0),-1)

#1.dst 2.center 3.r 
cv2.circle(dst,(250,250),(50),(0,255,0),2)

#1.dst 2.center 3.轴 4.偏转角度 5.起始角度 6.终止角度
cv2.ellipse(dst,(256,256),(150,100),0,0,180,(255,255,0),-1)

points = np.array([[150,50],[140,140],[200,170],[250,250],[150,50]],np.uint8)
print(points.shape)
points = points.reshape((-1,1,2))
print(points.shape)
cv2.polylines(dst,np.int32([points]),True,(0,255,255))

cv2.imshow('dst',dst)
cv2.waitKey(0)

文字图片绘制

import cv2
import numpy as np
img = cv2.imread('image0.jpg',1)
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.rectangle(img,(200,100),(500,400),(0,255,0),3)
#1.dst 2.文字内容 3.坐标 4.font 5.font size 6.color 7.粗细 8.line typr
cv2.putText(img,'hello',(100,300),font,1,(200,100,255),2,cv2.LINE_AA)
cv2.imshow('src',img)
cv2.waitKey(0)

import cv2
img = cv2.imread('image0.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(0,height):
    for j in range(0,width):
        img[i+200,j+350] = imgResize[i,j]
cv2.imshow('src',img)
cv2.waitKey(0)