Text-to-Image Generation from Scratch

Welcome to the Text-to-Image Generation project! This repository contains a complete implementation of a model that generates images from textual descriptions. We build everything from scratch, using custom neural networks and integrating them with a web application.

Project Overview

This project includes:

• Model Architecture: Custom neural network models for generating images from text descriptions.
• Training Scripts: Code to train the model on your own data.
• Evaluation: Metrics to assess the quality of generated images.
• Web Interface: An interactive webpage to input text and view generated images.

Features

• Train your own model using custom architectures.
• Interactive web interface for text-to-image generation.
• Metrics for evaluating image quality, including FID and BLEU scores.
• Modular and clean codebase with separate components for data handling, model building, training, evaluation, and web integration.

Installation

Prerequisites

• Python 3.8 or higher
• Flask
• PyTorch
• Other Python dependencies listed in requirements.txt

Setup

1. Clone the repository:

   git clone https://github.com/Gaurav-Jaiswal-1/Text2Image-Generation.git
   cd text-to-image-generation

2. Install dependencies:

   pip install -r requirements.txt

Usage

Training the Model

1. Preprocess the Data: Prepare your dataset by running:

   python scripts/preprocess_data.py

2. Train the Model: Start training the model with:

   python training/train.py --config config.yaml

3. Monitor Training: Use TensorBoard to visualize the training process:

   tensorboard --logdir logs/

Running the Web Application

1. Start the Backend Server:

   python web/backend/server.py

2. Access the Web Interface: Open your web browser and go to http://localhost:5000 to use the interactive text-to-image generation interface.

Generating Images from Text

To generate images without using the web interface:

python scripts/generate_images.py --text "A sunny beach with palm trees"

Evaluating the Model

Assess the quality of the generated images:

python evaluation/evaluate.py --model checkpoints/generator.pth

Project Structure

text-to-image-generation/
├── data/                 # Datasets and preprocessing scripts
├── models/               # Custom neural network models
├── training/             # Training scripts and loss functions
├── evaluation/           # Evaluation metrics and visualization
├── web/                  # Web application (frontend and backend)
├── utils/                # Utility functions (logging, checkpointing, etc.)
├── scripts/              # Utility scripts (data processing, etc.)
├── tests/                # Unit tests for various components
├── docs/                 # Documentation
├── requirements.txt      # Python dependencies
├── setup.py              # Installation script
├── README.md             # Project overview (you are here)
└── CONTRIBUTING.md       # Contribution guidelines

Documentation

• README.md: Overview and instructions.
• CONTRIBUTING.md: How to contribute to this project.
• docs/CHANGELOG.md: Change log for tracking updates.

Contributing

We welcome contributions to enhance this project. Please refer to the CONTRIBUTING.md for details on how to get involved.

License

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

Contact

For any questions or issues, please open an issue on this repository or contact us at jaiswalgaurav863@gmail.com