📋 Project Overview & Problem Statement
Challenge: Professional photo editing requires specialized skills and expensive software, creating barriers for content creators, small businesses, and individuals who need high-quality image enhancement for social media, marketing, or personal use.
Solution: Gemini Image Editor democratizes professional photo editing by leveraging Google's Gemini AI to provide intelligent, automated image enhancement tools that deliver professional results with simple, intuitive controls.
Key Benefits
- AI-Powered Enhancement: Intelligent photo optimization using advanced computer vision
- Professional Quality: Achieve professional-grade results without technical expertise
- Real-Time Processing: Instant preview and adjustment of editing effects
- Intuitive Interface: User-friendly design accessible to all skill levels
- Cloud-Based: No software installation required, works in any modern browser
🛠️ Technical Architecture & Implementation
Frontend Architecture
React 19
TypeScript 5.0
Vite Build Tool
Canvas API
WebGL Shaders
AI & Image Processing
Google Gemini AI
Computer Vision
Image Recognition
Color Theory AI
Filter Algorithms
Deployment & Infrastructure
Google Cloud Run
Docker Containers
CDN Integration
Auto Scaling
Load Balancing
System Architecture
Image Processing Pipeline:
- Secure image upload with format validation and size optimization
- Canvas-based image rendering and manipulation
- Gemini AI integration for intelligent enhancement recommendations
- Real-time filter application using WebGL shaders
- High-quality image export with format selection
📖 Development Setup & Installation Guide
Prerequisites
- Node.js 16+ with npm package manager
- Gemini API Key from Google AI Studio
- Modern Browser with Canvas and WebGL support
- Development Tools: VS Code with TypeScript extensions
Quick Start Installation
# Clone the repository
git clone https://github.com/lyven81/ai-project.git
cd ai-project/projects/gemini-image-editor
# Install dependencies
npm install
# Set up environment variables
cp .env.example .env
# Add your Gemini API key to .env
# Run development server
npm run dev
# Build for production
npm run build
Environment Configuration
# Required API Configuration
VITE_GEMINI_API_KEY=your_gemini_api_key_here
# Optional Application Settings
VITE_MAX_FILE_SIZE=10485760
VITE_SUPPORTED_FORMATS=jpeg,jpg,png,webp
VITE_DEBUG_MODE=false
🚀 Deployment Options & Production Configuration
Google Cloud Run Deployment (Recommended)
# Build and deploy using Cloud Build
gcloud builds submit --config cloudbuild.yaml
# Direct deployment
gcloud run deploy gemini-image-editor \
--image gcr.io/PROJECT-ID/gemini-image-editor \
--platform managed \
--region us-west1 \
--set-env-vars VITE_GEMINI_API_KEY=your_api_key
Alternative Deployment Methods
- Vercel: Direct GitHub integration with automatic deployments
- Netlify: Simple drag-and-drop deployment with CDN
- Docker: Containerized deployment for any cloud provider
- Static Hosting: Build and deploy to any static hosting service
Production Optimizations
- Performance: WebGL acceleration and optimized image processing
- Caching: Aggressive caching of processed images and AI results
- Security: Input validation, file type checking, and size limits
- Monitoring: Performance tracking and error reporting