AI Image Generator

A powerful web application that leverages Stable Diffusion models to generate stunning AI artwork from text prompts. Built with a modern tech stack focusing on performance and user experience.

Features

• Text-to-Image Generation: Transform your ideas into visual art
• Style Transfer: Apply artistic styles to your images
• Image Enhancement: Upscale and enhance generated images
• Gallery Mode: Browse and save your creations
• Batch Processing: Generate multiple variations at once

Architecture

The application follows a microservices architecture:

$$\text{Latency} = \sum_{i=1}^{n} (T_{\text{process}} + T_{\text{network}})$$

Where $T_{\text{process}}$ represents the processing time for each request and $T_{\text{network}}$ accounts for network overhead.

Tech Stack

Frontend

• React 18 - UI framework
• TypeScript - Type safety
• Tailwind CSS - Styling
• Zustand - State management

Backend

• Python FastAPI - API server
• Stable Diffusion - Image generation model
• Redis - Job queue management
• PostgreSQL - Data persistence

Model Details

The image generation uses a diffusion process:

$$x_t = \sqrt{\bar{\alpha}_t} x_0 + \sqrt{1 - \bar{\alpha}_t} \epsilon$$

Where $x_0$ is the original image, $\epsilon$ is Gaussian noise, and $\bar{\alpha}_t$ controls the noise schedule.

Screenshots

Main dashboard with generation controls

Generated image gallery

Video Demo

Installation

# Clone the repository
git clone https://github.com/yourusername/ai-image-generator.git

# Install dependencies
npm install

# Set up environment variables
cp .env.example .env

# Start the development server
npm run dev

Configuration

The application requires the following environment variables:

OPENAI_API_KEY=your_api_key
DATABASE_URL=postgresql://localhost:5432/ai_images
REDIS_URL=redis://localhost:6379

Performance Optimization

We implemented several optimizations:

1. Model Quantization: Reduced model size by 4x
2. Batch Inference: Process multiple prompts simultaneously
3. Caching: Redis-based caching for repeated prompts
4. CDN: Image delivery via CloudFlare CDN

Results

After optimization, we achieved:

Metric	Before	After
Generation Time	12s	3.5s
Memory Usage	8GB	4GB
API Latency	500ms	120ms

Future Plans

• Support for video generation
• Fine-tuning capabilities
• Mobile app release
• API for third-party integration

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This project was built as part of my exploration into generative AI. Feel free to check out the source code or try the live demo!