rajarshidattapy / celebrity-image-generation_hackai

The Celebrity Image Generation project leverages deep learning to generate realistic images of celebrities. Using a Flask backend and Python, this project provides a user-friendly interface for generating and exploring AI-generated celebrity faces.

Celebrity-Image-Generation

Celebrity Image Generation

The Celebrity Image Generation project leverages deep learning to generate realistic images of celebrities. Using a Flask backend and Python, this project provides a user-friendly interface for generating and exploring AI-generated celebrity faces.

Overview

This project showcases the power of Generative Adversarial Networks (GANs) in generating high-quality celebrity images. The system allows users to customize various facial attributes such as age, hairstyle, and gender, providing a highly interactive experience.

Table of Contents

• Features
• Tech Stack
• Architecture
• Installation
• Usage
• Model Details
• Contributing
• License
• Contact

Features

• Image Generation: Generate high-quality images of celebrities.
• Customization: Modify facial attributes (e.g., age, hairstyle) for generated images.
• User Interface: A simple web interface to interact with the model.
• API Access: Expose an API endpoint for generating images programmatically.

Tech Stack

• Backend: Flask, Python
• Machine Learning: TensorFlow, Keras, PyTorch
• Frontend: HTML, CSS, JavaScript (optional)
• Others: Docker (for containerization)

Architecture

Installation

Prerequisites

• Python 3.7+
• Virtual environment (recommended)
• Docker (optional)

Setup

1. Clone the repository:

   git clone https://github.com/your-username/celebrity-image-generation.git
   cd celebrity-image-generation

2. Create a virtual environment and activate it:

   python -m venv venv
   source venv/bin/activate   # On Windows use `venv\Scripts\activate`

3. Install dependencies:

   pip install -r requirements.txt

4. Set up environment variables:

   Create a .env file in the root directory and add any necessary configuration variables.

5. Run the application:

   flask run

6. Access the application:

   Open your browser and navigate to http://localhost:5000.

Usage

• Web Interface: Interact with the model using the provided web interface.

• API: Use the API to generate images programmatically.

  POST /api/generate
  Content-Type: application/json
  {
      "attributes": {
          "age": 30,
          "hairstyle": "short",
          "gender": "female"
      }
  }

Model Details

The model is based on GANs (Generative Adversarial Networks) trained on a dataset of celebrity images. For more details on the model architecture and training process, refer to the Model Documentation.

Contributing

We welcome contributions! Please read our Contributing Guidelines for more details.

License

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