DeepGIS XR

A Django-based geospatial platform for extended reality (XR) applications with integrated GIS capabilities, machine learning support, and real-time data processing.

Features

• Geospatial Processing: Built on GDAL/OGR with support for various spatial data formats
• Tile Server Integration: Built-in MapTiler tile server for high-performance map serving
• Machine Learning Ready: Includes PyTorch and scikit-image for ML/AI processing
• Real-time Processing: Celery integration for asynchronous task processing
• REST API: Full REST API support through Django REST framework
• Cross-Origin Support: Configured CORS headers for web and mobile clients
• Spatial Database: SQLite with SpatiaLite extension for spatial data storage

Architecture

The application consists of two main services:

1. Web Service

   • Django application (Port 8090)
   • Handles API requests, data processing, and ML tasks
   • Serves static and media files
   • Manages user authentication and data access

2. Tile Server

   • MapTiler TileServer-GL (Port 8091)
   • Serves vector and raster tiles
   • Supports multiple tile formats (MVT, PNG, JPEG, WebP)
   • CORS-enabled for cross-origin requests

Prerequisites

• Docker and Docker Compose
• GDAL 3.0+ (installed automatically in container)
• Python 3.9+
• 4GB+ RAM recommended
• SSD storage recommended for tile serving

Installation

1. Clone the repository:

   git clone https://github.com/your-org/deepgis-xr.git
   cd deepgis-xr

2. Build and start the services:

   docker-compose up --build

3. Access the services:

   • Web Application: http://localhost:8060
   • Tile Server: http://localhost:8091

Project Structure

deepgis-xr/
├── data/               # Tile server data directory
├── deepgis_xr/        # Django project directory
├── media/             # User uploaded files
├── static/            # Static files
├── staticfiles/       # Collected static files
├── Dockerfile         # Web service container definition
├── docker-compose.yml # Service orchestration
├── requirements.txt   # Python dependencies
└── config.json        # Tile server configuration

Configuration

Django Settings

• Set in deepgis_xr/settings.py
• Override using environment variables
• Debug mode controlled via DEBUG environment variable

Tile Server

• Configuration in config.json
• Supports custom styles and data sources
• CORS enabled by default for development

Development

1. Start services in development mode:

   docker-compose up

2. Run migrations:

   docker-compose exec web python manage.py migrate

3. Create superuser:

   docker-compose exec web python manage.py createsuperuser

API Endpoints

The REST API provides endpoints for:

• Spatial data upload and processing
• Tile generation and serving
• Machine learning model inference
• User management and authentication

Detailed API documentation available at /api/docs/ when running the server.

Dependencies

Core

• Django 3.2.24
• Django REST Framework 3.12.4
• GDAL/OGR (via system packages)
• Celery 5.2+ with Redis

Geospatial

• Rasterio 1.3.0
• Shapely 1.8.0
• Fiona 1.9.1
• GeoPandas 0.12.0
• PyProj 3.5.0

Machine Learning

• PyTorch
• TorchVision
• scikit-image

Production Deployment

For production deployment:

1. Update config.json with production domains
2. Set appropriate environment variables:

   DEBUG=False
   DJANGO_SETTINGS_MODULE=deepgis_xr.settings

3. Use proper SSL/TLS certificates
4. Configure proper authentication
5. Set up monitoring and logging

Contributing

1. Fork the repository
2. Create a feature branch
3. Submit a pull request

License

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

Support

For support and questions:

1. Open an issue in the repository
2. Contact the maintainers
3. Check the documentation in the /docs directory