🌟 Image Search Engine

Welcome to the Image Search Engine repository! This project offers a semantic image search engine that leverages advanced technologies such as CLIP and FAISS. Users can search for images based on text descriptions or visual similarities.

Table of Contents

• Features
• Technologies Used
• Installation
• Usage
• Contributing
• License
• Contact

Features

• Text-based Search: Find images by entering descriptive text.
• Visual Similarity Search: Search for images that are visually similar to a provided image.
• Fast Retrieval: Utilize FAISS for quick and efficient image retrieval.
• User-friendly Interface: Built with Flask for a smooth user experience.
• Deep Learning Integration: Leverage CLIP for understanding image semantics.

Technologies Used

• CLIP: A model developed by OpenAI for connecting images and text.
• FAISS: A library for efficient similarity search and clustering of dense vectors.
• Flask: A lightweight web framework for building the web interface.
• Python: The primary programming language used for development.
• Deep Learning: Techniques used for image understanding and retrieval.

Installation

To get started, you need to clone the repository and install the required packages. Follow these steps:

1. Clone the repository:

   git clone https://github.com/Patrick48777/Image-search-engine.git
   cd Image-search-engine

2. Install the required packages:

   pip install -r requirements.txt

3. Download the latest release and execute the necessary files. You can find the releases here.

Usage

Once you have installed the project, you can start the server and use the image search engine.

1. Start the Flask server:

   python app.py

2. Open your web browser and go to http://127.0.0.1:5000.

3. Use the search bar to enter text descriptions or upload an image for visual similarity search.

Contributing

We welcome contributions to improve the project. If you want to contribute, please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Make your changes and commit them.
4. Push to your forked repository.
5. Create a pull request.

Please ensure your code follows the project's coding style and includes appropriate tests.

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Contact

For any questions or feedback, feel free to reach out:

• Email: [email protected]
• GitHub: Patrick48777

Thank you for checking out the Image Search Engine! We hope you find it useful for your image retrieval needs. Don't forget to check the Releases section for updates and new features!