OpenCV Python 图像处理教程

Welcome to the OpenCV Python image processing tutorial. This guide will help you understand the basics of image processing using OpenCV with Python.

图像处理基础

图像读取与显示

To read an image, you can use the cv2.imread() function. To display an image, use cv2.imshow().

import cv2

# 读取图像
image = cv2.imread('image.jpg')

# 显示图像
cv2.imshow('Image', image)
cv2.waitKey(0)
cv2.destroyAllWindows()

图像操作

You can perform various operations on images such as resizing, cropping, and more.

# 调整图像大小
resized_image = cv2.resize(image, (100, 100))

# 裁剪图像
cropped_image = image[100:200, 100:200]

高级图像处理

边缘检测

Edge detection is a fundamental step in image processing. OpenCV provides various methods for edge detection.

# 使用Canny边缘检测
edges = cv2.Canny(image, 100, 200)

颜色转换

You can convert images from one color space to another using OpenCV functions.

# 转换为灰度图像
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

图像滤波

Image filtering is used to remove noise from images.

# 使用高斯滤波
blurred_image = cv2.GaussianBlur(image, (5, 5), 0)

学习资源

For more in-depth learning, you can refer to the OpenCV Python教程.

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