opencv-02-图像操作

图像操作

图像定义

RGB图像由格式为M×N×3的三维数组组成,其中的“3”可以理解为三幅M×N的二维图像(灰度值图像)。这三幅图像分别代表R、G、B分量,每个分量的像素点取值范围是[0,255]。

图像读取

  • cv2.IMREAD_COLOR:彩色图像
  • cv2.IMREAD_GRAYSCALE:灰度图像
import cv2 #opencv读取的格式是BGR
import matplotlib.pyplot as plt
import numpy as np 
%matplotlib inline 

img=cv2.imread('cat.jpg')
array([[[142, 151, 160],
        [146, 155, 164],
        [151, 160, 169],
        ...,
        [156, 172, 185],
        [155, 171, 184],
        [154, 170, 183]],

       [[107, 118, 126],
        [112, 123, 131],
        [117, 128, 136],
        ...,
        [155, 171, 184],
        [154, 170, 183],
        [153, 169, 182]],

       [[108, 119, 127],
        [112, 123, 131],
        [118, 129, 137],
        ...,
        [154, 170, 183],
        [153, 169, 182],
        [152, 168, 181]],

       ...,

       [[162, 186, 198],
        [157, 181, 193],
        [142, 166, 178],
        ...,
        [181, 204, 206],
        [170, 193, 195],
        [149, 172, 174]],

       [[140, 164, 176],
        [147, 171, 183],
        [139, 163, 175],
        ...,
        [167, 187, 188],
        [123, 143, 144],
        [104, 124, 125]],

       [[154, 178, 190],
        [154, 178, 190],
        [121, 145, 157],
        ...,
        [185, 198, 200],
        [130, 143, 145],
        [129, 142, 144]]], dtype=uint8)

显示图像

#图像的显示,也可以创建多个窗口
cv2.imshow('image',img) 
# 等待时间,毫秒级,0表示任意键终止
cv2.waitKey(0) 
# 等待一个键结束类似于C语言的system("pause")
cv2.destroyAllWindows()

img=cv2.imread('cat.jpg',cv2.IMREAD_GRAYSCALE)

灰度图

array([[153, 157, 162, ..., 174, 173, 172],
       [119, 124, 129, ..., 173, 172, 171],
       [120, 124, 130, ..., 172, 171, 170],
       ...,
       [187, 182, 167, ..., 202, 191, 170],
       [165, 172, 164, ..., 185, 141, 122],
       [179, 179, 146, ..., 197, 142, 141]], dtype=uint8)

截取部分图像

img=cv2.imread('cat.jpg')
cat=img[0:50,0:200] 
cv_show('cat',cat)

img=cv2.imread('cat.jpg')
cat=img[0:50,0:200] 
cv_show('cat',cat)

b,g,r=cv2.split(img)
img=cv2.merge((b,g,r))
img.shape
# 只保留R
cur_img = img.copy()
cur_img[:,:,0] = 0
cur_img[:,:,1] = 0
cv_show('R',cur_img)

# 只保留G
cur_img = img.copy()
cur_img[:,:,0] = 0
cur_img[:,:,2] = 0
cv_show('G',cur_img)

# 只保留B
cur_img = img.copy()
cur_img[:,:,1] = 0
cur_img[:,:,2] = 0
cv_show('B',cur_img)

边界填充

top_size,bottom_size,left_size,right_size = (50,50,50,50)

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,cv2.BORDER_REFLECT)
reflect101 = cv2.copyMakeBorder(img, top_size, bottom_size, left_size, right_size, cv2.BORDER_REFLECT_101)
wrap = cv2.copyMakeBorder(img, top_size, bottom_size, left_size, right_size, cv2.BORDER_WRAP)
constant = cv2.copyMakeBorder(img, top_size, bottom_size, left_size, right_size,cv2.BORDER_CONSTANT, value=0)

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('REFLECT_101')
plt.subplot(235), plt.imshow(wrap, 'gray'), plt.title('WRAP')
plt.subplot(236), plt.imshow(constant, 'gray'), plt.title('CONSTANT')

plt.show()

数值计算

img_cat=cv2.imread('cat.jpg')
img_dog=cv2.imread('dog.jpg')
img_cat2= img_cat +10 # 每个位置都加10
img_cat[:5,:,0]
array([[142, 146, 151, ..., 156, 155, 154],
       [107, 112, 117, ..., 155, 154, 153],
       [108, 112, 118, ..., 154, 153, 152],
       [139, 143, 148, ..., 156, 155, 154],
       [153, 158, 163, ..., 160, 159, 158]], dtype=uint8)
       
       
     

img_cat2[:5,:,0]

  array([[152, 156, 161, ..., 166, 165, 164],
       [117, 122, 127, ..., 165, 164, 163],
       [118, 122, 128, ..., 164, 163, 162],
       [149, 153, 158, ..., 166, 165, 164],
       [163, 168, 173, ..., 170, 169, 168]], dtype=uint8)

#相当于% 256 (img_cat + img_cat2)[:5,:,0]

array([[ 38,  46,  56, ...,  66,  64,  62],
       [224, 234, 244, ...,  64,  62,  60],
       [226, 234, 246, ...,  62,  60,  58],
       [ 32,  40,  50, ...,  66,  64,  62],
       [ 60,  70,  80, ...,  74,  72,  70]], dtype=uint8)
cv2.add(img_cat,img_cat2)[:5,:,0]

图像融合

如果直接加shape不同,无法加

img_cat + img_dog

image-20200316125028303

视频操作

  • cv2.VideoCapture可以捕获摄像头,用数字来控制不同的设备,例如0,1。
  • 如果是视频文件,直接指定好路径即可。

数据读取

vc = cv2.VideoCapture('test.mp4')
# 检查是否打开正确
if vc.isOpened(): 
    oepn, 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)
        cv2.imshow('result', gray)
        if cv2.waitKey(100) & 0xFF == 27:
            break
vc.release()
cv2.destroyAllWindows()

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转载自blog.csdn.net/jankin6/article/details/105293969
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