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opencv学习笔记二——图像基本操作

2022-07-07 05:19:00 【我是一个小稻米】

1. POI区域：感兴趣区域

2. 边缘填充

3. 数值运算

import cv2
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
from PIL import Image

image1 = mpimg.imread('1.jpg')
image2 = mpimg.imread('2.jpg')

plt.imshow(image1)

请添加图片描述

plt.imshow(image2)

请添加图片描述

图像加法

image3 = image1+image2
plt.imshow(image3)

请添加图片描述

图像裁剪

plt.imshow(image1[100:-100, 100:-100, :]);

请添加图片描述

图像缩放

fx和fy表示缩放倍数

image4 = cv2.resize(image1, (0, 0), fx=3, fy=1)
plt.imshow(image4);

请添加图片描述

4. 图像阈值

ret, dst = cv2.threshold(src, thresh, maxval, type)

src: 输入图像，只能是单通道图像
dst：输出图
thresh：阈值
maxval：当像素值超过了阈值或小于阈值时的取值
type：二值化的类型
- cv2.THRESH_BINARY 超过阈值取maxval，否则取0
- cv2.THRESH_BINARY_INV THRESH_BINARY的反转
- cv2.THRESH_TRUNC 大于阈值设置阈值，其余不变
- cv2.THRESH_TOZERO 大于阈值不变，其余设为0
- cv2.THRESH_TOZERO_INV THRESH_TOZERO的反转

image1_gray = image1[:,:,0]
res, thresh1 = cv2.threshold(image1_gray, 127, 255, cv2.THRESH_BINARY)
res, thresh2 = cv2.threshold(image1_gray, 127, 255, cv2.THRESH_BINARY_INV)
res, thresh3 = cv2.threshold(image1_gray, 127, 255, cv2.THRESH_TRUNC)
res, thresh4 = cv2.threshold(image1_gray, 127, 255, cv2.THRESH_TOZERO)
res, thresh5 = cv2.threshold(image1_gray, 127, 255, cv2.THRESH_TOZERO_INV)

titles = ['Original Image', 'BINARY', 'BINARY_INV', 'TRUNC', 'TOZERO', 'TOZERO_INV']
images = [image1_gray, thresh1, thresh2, thresh3, thresh4, thresh5]
for i in range(6):
    plt.subplot(2,3,i+1)
    plt.imshow(images[i], 'gray')
    plt.title(titles[i])
    plt.xticks([])
    plt.yticks([])
plt.show()