Add Advanced Video Analytics Research Pipeline template

[ldmdldm]

Advanced Video Analytics Research Pipeline Template

Overview

This Pull Request introduces a video analytics research pipeline template for the Nosana platform. The template combines computer vision models with advanced research for both academic research and industrial applications.

Our Features

• Multi-model ensemble support with YOLOv8 and ByteTrack integration
• Advanced experiment tracking and metrics collection
• Distributed processing capabilities
• Edge computing support
• Comprehensive research tools integration (TensorBoard, Weights & Biases, MLflow)
• Custom model integration support
• Detailed performance metrics and analysis tools

Technical Details

• GPU architecture
• Live processing capabilities
• Configurable research and production modes
• Extensive metrics collection and analysis
• Support for various data formats and export options

Use Cases

• Academic research in computer vision
• Industrial R&D for video analytics
• Security and surveillance systems
• Retail analytics
• Traffic monitoring
• Sports analytics
• Industrial automation
• Edge computing deployments

Files Added

• job-definition.json: Core job configuration
• info.json: Template metadata and display information
• README.md: Comprehensive documentation

Testing

The template has been tested with:

• Various video input sources
• Different model configurations
• Multiple GPU setups
• Edge computing scenarios

Documentation

Detailed documentation is provided in the README.md file, including:

• Research capabilities
• Technical architecture
• Getting started guide
• Example workflows
• Citation information

Dependencies

• CUDA-enabled GPU
• 32GB RAM minimum
• 50GB storage
• Network connectivity for RTSP streams

Impact

This template significantly enhances the Nosana platform's capabilities for:

• Research and development in computer vision
• Industrial video analytics applications
• Edge computing research
• Distributed video processing

Future Improvements

• Additional model integrations
• Enhanced edge computing capabilities
• More research tools integration
• Extended documentation and examples