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Host : https://text2picapp.netlify.app/


GAN-Based Text-to-Image Synthesizer

A deep learning-based project that generates high-quality images from textual descriptions using Generative Adversarial Networks (GAN) and Latent Diffusion Models (LDM). This project enables users to input text and receive an AI-generated image based on the description.

Table of Contents

Features

  • Text-to-image conversion using GAN and LDM.
  • Pre-trained models for enhanced performance.
  • Web-based user interface for text input and image display.
  • Chatbot support for interactive user assistance.

Technologies Used

  • Backend: Python, PyTorch, Hugging Face
  • Frontend: React.js/Next.js
  • API Development: Node.js, Express.js
  • Database: SQL Server
  • Deployment: Docker, AWS/GCP

Installation

Clone the Repository

git clone https://github.com/your-repo-name.git
cd your-repo-name

Backend Setup

  1. Create a virtual environment:

    python -m venv venv
    source venv/bin/activate  # Linux/Mac
    venv\Scripts\activate  # Windows
  2. Install dependencies:

    pip install -r requirements.txt
  3. Download pre-trained models: Place the downloaded models in the models/ directory.

Frontend Setup

  1. Navigate to the frontend directory:
    cd frontend
  2. Install dependencies:
    npm install

Usage

Running the Backend

  1. Activate the virtual environment:
    source venv/bin/activate  # Linux/Mac
    venv\Scripts\activate  # Windows
  2. Start the backend server:
    python app.py

Running the Frontend

  1. Navigate to the frontend directory:
    cd frontend
  2. Start the development server:
    npm run dev

Accessing the Application

Open your browser and navigate to http://localhost:3000.

Build Commands

Build the Backend

python setup.py build

Build the Frontend

npm run build

Running Tests

  • Backend:
    pytest tests/
  • Frontend:
    npm test

Contributors

  • Supun Thilakshana - Text-to-Image Model Developer
  • Sachini - Web App Developer
  • Pavith - Chatbot Developer

License

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

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