🌟 Information Retrieval Project: Multimodal Search Engine 🌟

Download Latest Release

Overview

Welcome to the Information Retrieval Project: Multimodal Search Engine. This project integrates text and image embeddings to create a unified and efficient search engine. It leverages deep learning techniques to enhance the search experience across different data modalities.

Table of Contents

1. Introduction
2. Features
3. Technologies Used
4. Installation
5. Usage
6. Contributing
7. License
8. Contact

Introduction

In today's digital world, users often seek information in various formats. A multimodal search engine addresses this need by allowing users to search using both text and images. This project combines state-of-the-art techniques in computer vision and natural language processing to provide a seamless search experience.

Features

• Unified Search: Search through text and images simultaneously.
• Deep Learning Models: Utilizes advanced models for embedding generation.
• Efficient Retrieval: Fast and accurate search results.
• User-Friendly Interface: Simple and intuitive design for easy navigation.
• Extensible Architecture: Easy to add new features and functionalities.

Technologies Used

This project employs a range of technologies, including:

• Python: The primary programming language.
• PyTorch: Framework for building deep learning models.
• Machine Learning Libraries: For various ML tasks.
• Natural Language Processing: Techniques for processing text data.
• Computer Vision: Tools for image processing and analysis.

Installation

To set up the project on your local machine, follow these steps:

1. Clone the Repository:

   git clone https://github.com/shenqiongyu/Information-Retrieval-Project---Multimodal-Search-Engine.git
   cd Information-Retrieval-Project---Multimodal-Search-Engine

2. Install Dependencies:

   Ensure you have Python installed. Then, install the required packages:

   pip install -r requirements.txt

3. Download the Latest Release:

   For the latest version of the project, visit the Releases section. Download the necessary files and execute them.

Usage

Once the installation is complete, you can start using the multimodal search engine. Here’s how:

1. Run the Application:

   Execute the following command to start the server:

   python app.py

2. Access the Interface:

   Open your web browser and go to http://localhost:5000 to access the search interface.

3. Perform a Search:

   You can enter text queries or upload images to retrieve relevant results.

Contributing

We welcome contributions to enhance the functionality of this project. To contribute:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Commit your changes and push to your branch.
4. Open a pull request.

Please ensure that your code adheres to the existing style and includes relevant tests.

License

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

Contact

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

• Author: Shen Qiongyu
• Email: [email protected]
• GitHub: shenqiongyu

---

Thank you for checking out the Information Retrieval Project: Multimodal Search Engine! We hope you find it useful for your information retrieval needs. For updates, please visit the Releases section.