Framework Integration¶
PrimateFace provides integration with popular computer vision and pose estimation frameworks.
Overview¶
These guides help you use PrimateFace with external frameworks:
- MMDetection/MMPose - Primary framework for detection and pose estimation
- DeepLabCut - Alternative pose estimation with COCO training support
- SLEAP - Multi-animal tracking with COCO training support
- YOLO - Real-time detection and integration examples
Integration Approach¶
PrimateFace doesn't replace these frameworks - it provides:
- Training Scripts - Convert COCO data to framework-specific formats
- Model Compatibility - Use framework models with PrimateFace pipelines
- Evaluation Tools - Compare performance across frameworks
- Workflow Integration - Seamless integration with existing workflows
When to Use Each Framework¶
- MMDetection/MMPose - Production inference, best performance
- DeepLabCut - Markerless tracking, behavioral analysis
- SLEAP - Multi-animal scenarios, complex tracking
- YOLO - Real-time applications, edge deployment
Getting Started¶
Each framework has specific setup requirements. See the individual guides for:
- Installation and setup
- Training from COCO data
- Integration with PrimateFace
- Performance optimization
For detailed API documentation, see the API Reference.