Blend-O-Matic Motion Tracking & ML Video Labeling

Hey there,

I’m working on a project to seamlessly integrate Blender’s motion tracking with ML video annotation.

Harnessing tracking markers as primary annotation points, we aim for dynamic annotations that adjust with tracked objects, optimizing the video annotation process for ML.

Technical Approach:

  • Tracking Markers: Direct utilization of MovieClipTrackingTrack and MovieClipTrackingMarker.
  • Custom Properties: Embedding annotation metadata directly on markers.
  • Visualization: Real-time annotation visualization tools in the Movie Clip Editor.
  • Data Management: Systems for I/O of tracking and annotation data, targeting Pascal VOC format compatibility.


  • ML Model Comparison: Load and juxtapose overlays from different ML training sessions.
  • ML Output Refinement: In-Blender tools for editing and refining ML model outputs.
  • Interactive Annotation: Exploit motion tracking for on-the-fly annotation adjustments.
  • Collaborative Annotation: Features to bolster team-based annotation workflows.
  • Object & Pose Integration: Seamlessly import and refine object detection and pose detection results.
  • Segment Anything: integrating automatic object segmentation and pytorch with Blender.
  • Pie Menus: Intuitive pie menus for rapid label management, editing, and selection.
  • Streamlined UI: A user interface tailored for efficiency, minimizing clicks and maximizing productivity.
  • Extensibility: A modular design to allow future enhancements and integration with other ML tools.

Seeking Feedback On:

  • Challenges: Potential pitfalls or challenges with this approach?
  • Overlap: Know of any Blender projects or tools that might intersect with this?
  • Technical Recommendations: Pointers on APIs, data structures, or best practices, especially around motion tracking?

Your insights would be invaluable. Thanks for your time – Blend on!


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