# PyCV-Basics

**Repository Path**: joy_2_0/python-cv-basics

## Basic Information

- **Project Name**: PyCV-Basics
- **Description**: 该项目收录了多个基于 Python + OpenCV 的图像处理基础示例，包括：Canny 边缘检测、图像镜像翻转（水平 / 垂直 / 对角）、饱和度调节（RGB → HSL 思路模拟 Photoshop 效果）。所有脚本均结构简单、易读，适合作为图像处理课程作业、入门学习或算法可视化测试。
- **Primary Language**: Python
- **License**: Apache-2.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 0
- **Created**: 2025-11-22
- **Last Updated**: 2025-11-22

## Categories & Tags

**Categories**: Uncategorized

**Tags**: Canny边缘检测, 图像处理, 计算机视觉

## README

# PyCV-Basics  
*A lightweight collection of introductory computer vision exercises using Python and OpenCV.*

本项目收录了三个经典的图像处理入门示例，适用于初学者快速理解计算机视觉的基本操作，包括边缘检测、图像镜像与饱和度调整。所有示例均以简洁明了的 Python 代码呈现，便于学习与复现。

This repository contains three fundamental image processing examples implemented with Python and OpenCV. It is designed for beginners who wish to understand core computer vision operations through clear and minimal code samples.

---

## Project Structure / 项目结构

```text
PyCVBasics/
│
├── canny_edge_detection/
│     ├── Canny Edge Detection.py
│     ├── Girl.png
│     ├── canny1_result.png
│     └── canny2_result.png
│
├── image_mirroring/
│     ├── Image Mirroring.py
│     ├── Girl.png
│     ├── Girl_horizontal.png
│     ├── Girl_vertical.png
│     └── Girl_diagonal.png
│
├── saturation_adjustment/
│     ├── Saturation Adjustment.py
│     ├── Girl.png
│     ├── Low_saturated.png
│     └── High_saturated.png
```


## Included Modules / 模块说明

### 1. Canny Edge Detection  
Demonstrates classical Canny operator for extracting image edges.  
展示经典 Canny 算子用于提取图像边缘。

### 2. Image Mirroring  
Applies horizontal, vertical, and diagonal image mirroring transformations.  
实现水平、垂直、对角线的图像镜像变换。

### 3. Saturation Adjustment  
Illustrates HSV-based saturation enhancement and reduction.  
基于 HSV 色彩空间的图像饱和度提升与降低示例。

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## Requirements / 环境依赖

- Python 3.x  
- OpenCV (`pip install opencv-python`)

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## Purpose / 项目目的

该项目旨在为初学者提供最小化、易读、可复现的计算机视觉入门案例，帮助理解图像处理的核心思想，并为后续更复杂的深度学习与视觉算法打下基础。

This repository serves as a concise entry point for beginners to explore essential image processing techniques and prepare for more advanced CV or deep learning tasks.

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## License / 许可协议

This project is provided for learning and reference.  
本项目用于学习与参考使用。