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https://github.com/princesuchak/foxel

Foxel 是一个基于 .NET 9 开发的现代化智能图像检索与管理系统,集成先进的 AI 视觉模型 和 向量嵌入技术,提供高效的图像搜索与管理功能。
https://github.com/princesuchak/foxel

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Foxel 是一个基于 .NET 9 开发的现代化智能图像检索与管理系统,集成先进的 AI 视觉模型 和 向量嵌入技术,提供高效的图像搜索与管理功能。

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README

          

# Foxel: Modern Intelligent Image Retrieval and Management System 🦊📸

![Foxel Logo](https://via.placeholder.com/150)

Welcome to **Foxel**, a modern image retrieval and management system built on .NET 9. Foxel integrates advanced AI vision models and vector embedding techniques to deliver efficient image search and management functionalities.

## Table of Contents

1. [Introduction](#introduction)
2. [Features](#features)
3. [Technologies Used](#technologies-used)
4. [Installation](#installation)
5. [Usage](#usage)
6. [Contributing](#contributing)
7. [License](#license)
8. [Contact](#contact)
9. [Releases](#releases)

## Introduction

Foxel provides a seamless way to manage and search images using cutting-edge technology. It allows users to quickly find the images they need, making it an essential tool for photographers, designers, and anyone who handles a large number of images. With its user-friendly interface and powerful backend, Foxel simplifies the image management process.

## Features

- **Intelligent Image Search**: Utilize AI-driven algorithms to find images based on visual similarity.
- **Efficient Management**: Organize images into galleries and collections for easy access.
- **Responsive Design**: Access Foxel on any device, ensuring a smooth experience whether on desktop or mobile.
- **Customizable**: Tailor the system to fit your specific needs with flexible settings.
- **Secure**: Protect your images with robust security measures.

## Technologies Used

Foxel is built using a combination of the following technologies:

- **.NET 9**: The core framework for building the application.
- **C#**: The primary programming language used in development.
- **React**: For creating a dynamic user interface.
- **TypeScript**: Enhances JavaScript with type safety.
- **AI Vision Models**: Advanced algorithms for image recognition and retrieval.
- **Vector Embedding Techniques**: Efficient methods for image comparison.

## Installation

To get started with Foxel, follow these steps:

1. **Clone the Repository**:
```bash
git clone https://github.com/princesuchak/Foxel.git
```

2. **Navigate to the Project Directory**:
```bash
cd Foxel
```

3. **Install Dependencies**:
```bash
dotnet restore
```

4. **Build the Project**:
```bash
dotnet build
```

5. **Run the Application**:
```bash
dotnet run
```

You can also download the latest release from the [Releases section](https://github.com/princesuchak/Foxel/releases) and execute the provided binaries for a quick setup.

## Usage

Once you have installed Foxel, you can start using it right away. Here’s how:

1. **Upload Images**: Use the upload feature to add images to your gallery.
2. **Search for Images**: Utilize the search bar to find images based on keywords or visual similarity.
3. **Manage Galleries**: Organize your images into different galleries for better management.
4. **Customize Settings**: Adjust settings to tailor the experience to your needs.

## Contributing

We welcome contributions to Foxel! If you want to help improve the project, please follow these steps:

1. **Fork the Repository**: Click the "Fork" button on the top right of the repository page.
2. **Create a New Branch**:
```bash
git checkout -b feature/YourFeatureName
```
3. **Make Your Changes**: Edit the code and commit your changes.
4. **Push to Your Fork**:
```bash
git push origin feature/YourFeatureName
```
5. **Create a Pull Request**: Go to the original repository and click on "New Pull Request".

## License

Foxel is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.

## Contact

For questions or suggestions, feel free to reach out:

- **Email**: your-email@example.com
- **GitHub**: [princesuchak](https://github.com/princesuchak)

## Releases

To download the latest version of Foxel, visit the [Releases section](https://github.com/princesuchak/Foxel/releases). You can find the necessary files to download and execute.

## Conclusion

Foxel represents a significant step forward in image management and retrieval. With its advanced features and user-friendly design, it stands out as a valuable tool for anyone who works with images. We encourage you to explore the system and contribute to its ongoing development.

![Foxel Image Management](https://via.placeholder.com/800x400)

Feel free to dive into the code, explore the features, and join our community of developers and users. Your feedback and contributions are essential to making Foxel even better.