Retail Asset Creation Platform

A comprehensive Next.js application for AI-powered retail asset creation and management, providing an intuitive user interface to generate, manipulate, and manage retail product imagery.

Demo

Watch the demo video above to see the Retail Asset Creation Platform in action, showcasing model generation, virtual try-on, background manipulation, and catalog creation features.

Features

• Model Generation - Create realistic human models with customizable attributes (body size, skin color, age)
• Virtual Try-On - Visualize clothing items on model images with AI-powered fitting
• Background Generation - Create custom backgrounds for product images
• Background Removal - Automatically remove backgrounds from product images
• Image Tagging - Automatically tag and analyze retail images using AI
• Catalog Generation - Create professional product catalogs with AI-generated assets
• Gallery Management - Store, organize, and reuse all generated assets
• Multi-Model Support - Integration with multiple AI providers and models for different tasks

Technologies

Frontend

• Next.js - React framework
• TypeScript - Type-safe JavaScript
• Tailwind CSS - Utility-first CSS framework
• shadcn/ui - UI component library
• React Hook Form - Form handling
• Zod - Schema validation

Backend

• FastAPI - High-performance Python web framework
• Leonardo.ai - AI model generation API
• Fashn.ai - Virtual try-on API
• OpenAI - Image tagging and analysis
• Bria API - Background replacement

Setup

1. Install frontend dependencies:

   npm install

2. Install backend dependencies:

   cd fastapi_backend
   pip install -r requirements.txt

3. Configure environment variables:

   Frontend (.env.local):

   NEXT_PUBLIC_API_URL=http://localhost:8000
   NEXT_PUBLIC_LEONARDO_API_KEY=your_leonardo_api_key
   NEXT_PUBLIC_FASHN_API_KEY=your_fashn_api_key
   NEXT_PUBLIC_OPENAI_API_KEY=your_openai_api_key
   NEXT_PUBLIC_BRIA_API_KEY=your_bria_api_key
   

   Backend (.env in fastapi_backend directory):

   LEONARDO_API_KEY=your_leonardo_api_key
   FASHN_API_KEY=your_fashn_api_key
   OPENAI_API_KEY=your_openai_api_key
   BRIA_API_KEY=your_bria_api_key
   DATABASE_URL=postgresql://user:password@localhost:5432/dbname
   REDIS_URL=redis://localhost:6379
   

4. Database Setup:

   • Install PostgreSQL if not already installed
   • Create a new database
   • Run migrations:

     cd fastapi_backend
     alembic upgrade head

5. Redis Setup:

   • Install Redis if not already installed
   • Ensure Redis server is running locally or update REDIS_URL accordingly

6. Start the development servers:

   Frontend:

   npm run dev

   Backend:

   cd fastapi_backend
   python run.py

7. Build for production:

   npm run build

System Requirements

• Node.js 18.x or higher
• Python 3.9 or higher
• PostgreSQL 13 or higher
• Redis 6.x or higher
• At least 8GB RAM recommended for AI processing
• GPU recommended for faster processing (optional)

Application Structure

Frontend

• app/page.tsx - Home page with feature overview
• app/model-generation/ - AI model generation interface
• app/try-on/ - Virtual try-on interface
• app/background-generator/ - Background generation interface
• app/background-removal/ - Background removal interface
• app/image-tagging/ - Image tagging and analysis interface
• app/catalog-generator/ - Catalog generation interface
• app/gallery/ - Gallery to view all generated assets
• components/ - Reusable UI components
• services/ - API services for backend communication

Backend

• fastapi_backend/app/api/ - API endpoints and routers
• fastapi_backend/services/ - Service implementations for different features
• fastapi_backend/app/schemas/ - Data models and validation schemas

Features In Detail

Model Generation

Generate photorealistic human models with customizable attributes using Leonardo.ai's advanced models. Control body size, skin color, age, and other parameters to create perfect models for your product imagery.

Virtual Try-On

Visualize how clothing items will look on models using AI-powered fitting. Upload model images and garment images to see realistic try-on results.

Background Generation

Create custom backgrounds for product images based on textual descriptions. Generate professional studio settings, lifestyle environments, or any other background for your products.

Image Tagging

Automatically analyze and tag retail images using AI. Extract product attributes, descriptions, and other useful information from your product images.

Catalog Generation

Combine all assets to create professional product catalogs with consistent styling, backgrounds, and presentation.

API Integration

The application integrates with multiple AI providers:

• Leonardo.ai - For realistic model generation
• Fashn.ai - For virtual try-on functionality
• OpenAI - For image analysis and tagging
• Bria - For background replacement

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License.