OpenCV-图像基本操作 图像截取特定区域、颜色通道提取、边界填充、数值计算、图像融合_cv2取图片指定位置

将图片转换为像素的矩阵

图片

from matplotlib import pyplot as plt 的基本用法简介

import cv2
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline


img=cv2.imread('man.jpg')
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img
img
array([[[  2,   2,   2],
        [  2,   2,   2],
        [  2,   2,   2],
        ...,
        [ 20,  20,   6],
        [ 19,  19,   5],
        [ 27,  27,  13]],

       [[  2,   2,   2],
        [  2,   2,   2],
        [  2,   2,   2],
        ...,
        [ 15,  15,   9],
        [ 11,  11,   5],
        [  6,   7,   0]],

       [[  2,   2,   2],
        [  2,   2,   2],
        [  2,   2,   2],
        ...,
        [  6,   6,   6],
        [  4,   4,   4],
        [  7,   7,   7]],

       ...,

       [[196, 209, 217],
        [198, 211, 219],
        [201, 214, 222],
        ...,
        [240, 239, 241],
        [236, 235, 237],
        [239, 238, 240]],

       [[196, 209, 217],
        [198, 211, 219],
        [200, 213, 221],
        ...,
        [244, 243, 245],
        [238, 237, 239],
        [239, 238, 240]],

       [[198, 210, 216],
        [199, 211, 217],
        [197, 211, 217],
        ...,
        [236, 238, 238],
        [233, 235, 235],
        [237, 239, 239]]], dtype=uint8)
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cv2.imshow('image',image)
cv2.waitKey(0)
cv2.destoryAllWindows()
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image.shape
1

import cv2
image=cv2.imread('man.jpg',cv2.IMREAD_GRAYSCALE)#灰度图像，
image
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#保存 
cv2.imwrite('huiman.jpg',image)
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type(image)
1

image.size
1

image.dtype
1

视频

import cv2
vc = cv2.VideoCapture('scenery.MP4')
#检查是否可以正常打开
if vc.isOpened():
    open,frame=vc.read()
else:
    open = False
while open:
    ret,frame = vc.read()
    if frame is None:
        break
    if ret == True:
        gray=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)#将彩色视频转化为灰色视频
        cv2.imshow('result',gray)
        if cv2.waitKey(10)&0xFF==27:#括号中数字越大，视频播放速度越慢。0xFF==27表示按ESC后退出视频播放
          break
vc.release()
cv2.destoryAllWindows()
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图像截取特定的区域

这是数组类型， 0-200 指定切片，把想要的区域选择出来

import cv2

def cv_show(name,image):
    cv2.imshow(name,image)
    cv2.waitKey(0)
    cv2.destoryAllWindows()
    
image = cv2.imread('man.jpg')
man = image[0:200,0:200]
cv_show('man',man)
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颜色通道提取

import cv2

def cv_show(name,image):
    cv2.imshow(name,image)
    cv2.waitKey(0)
    cv2.destoryAllWindows()
    
image = cv2.imread('man.jpg')
man = image[200:630,250:450]
cv_show('man',man)
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B,G,R分离

import cv2
image = cv2.imread('man.jpg')
b,g,r=cv2.split(image)
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import cv2
import numpy as np
image = cv2.imread('man.jpg')
(B,G,R) = cv2.split(image)
image = cv2.merge([B,G,R])
cv2.imshow('image',image)
cv2.imshow("Red",R)
cv2.imshow("Green",G)
cv2.imshow("Blue",B)
cv2.waitKey(0)
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#只保留R
#只保留R
def cv_show(name,image):
    cv2.imshow(name,image)
    cv2.waitKey(0)
    cv2.destoryAllWindows()
    
cur_img = image.copy()
cur_img[:,:,0] = 0
cur_img[:,:,1] = 0
cv_show('R',cur_img)
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#只保留B
def cv_show(name,image):
    cv2.imshow(name,image)
    cv2.waitKey(0)
    cv2.destoryAllWindows()
    
cur_img = image.copy()
cur_img[:,:,2] = 0
cur_img[:,:,1] = 0
cv_show('B',cur_img)
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#只保留G
def cv_show(name,image):
    cv2.imshow(name,image)
    cv2.waitKey(0)
    cv2.destoryAllWindows()
    
cur_img = image.copy()
cur_img[:,:,0] = 0
cur_img[:,:,2] = 0
cv_show('G',cur_img)
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边界填充

import cv2
import numpy as np
img=cv2.imread('man.jpg')
top_size,bottom_size,left_size,right_size=(150,150,150,150)
replicate=cv2.copyMakeBorder(img,top_size,bottom_size,left_size,right_size,borderType=cv2.BORDER_REPLICATE)
reflect=cv2.copyMakeBorder(img,top_size,bottom_size,left_size,right_size,borderType=cv2.BORDER_REFLECT)
reflect101=cv2.copyMakeBorder(img,top_size,bottom_size,left_size,right_size,borderType=cv2.BORDER_REFLECT101)
wrap=cv2.copyMakeBorder(img,top_size,bottom_size,left_size,right_size,borderType=cv2.BORDER_WRAP)
constant=cv2.copyMakeBorder(img,top_size,bottom_size,left_size,right_size,borderType=cv2.BORDER_CONSTANT,value=0)#value=0黑框

import matplotlib.pyplot as plt
plt.subplot(231),plt.imshow(img,'gray'),plt.title('ORIGINAL')
plt.subplot(232),plt.imshow(replicate,'gray'),plt.title('REPLICATE')
plt.subplot(233),plt.imshow(reflect,'gray'),plt.title('REFLECT')
plt.subplot(234),plt.imshow(reflect101,'gray'),plt.title('REFLECT101')
plt.subplot(235),plt.imshow(wrap,'gray'),plt.title('WRAP')
plt.subplot(236),plt.imshow(constant,'gray'),plt.title('CONSTANTL')

plt.show()

# cv2.BORDER_REPLICATE复制法，复制最边缘像素
# cv2.BORDER_REFLECT反射法，对感兴趣的图像中的像素在两边进行入职
# cv2.BORDER_REFLECT101反射法，以最边缘像素为轴，对称 cv2.BORDER_WRAP外包装法
# cv2.BORDER_CONSTANT常良法
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数值计算

img_queen = cv2.imread('queen.jpg')
img_man = cv2.imread('man.jpg')
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img_man2 =img_man + 10 #在图像中每个像素点+10，
img_man[:5,:,0]
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img_man2[:5,:,0]
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(img_man + img_man2)[:5,:,0]
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cv2.add(img_man,img_man2)[:5,:,0]
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图像融合

res =cv2.addWeighted(img_man,0.4,img_queen,0.6,0.4)
plt.imshow(res)
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img_man=cv2.resize(img_man,(640,640))
img_man.shape
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res = cv2.resize(img,(0,0),fx=3,fy=1)
plt.imshow(res)
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res = cv2.resize(img,(0,0),fx=1,fy=3)
plt.imshow(res)
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res = cv2.resize(img,(0,0),fx=5,fy=5)
plt.imshow(res)
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