waldo_vision 0.2.0

A multi-layered computer vision engine for detecting significant events in real-time video streams.
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  • Source code size: 102.07 kB This is the summed size of all the files inside the crates.io package for this release.
  • Documentation size: 1.93 MB This is the summed size of all files generated by rustdoc for all configured targets
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  • this release: 32s Average build duration of successful builds.
  • all releases: 37s Average build duration of successful builds in releases after 2024-10-23.
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Waldo Vision Engine (waldo_vision)

waldo_vision is a multi-layered computer vision engine built from scratch in pure Rust. It is designed to detect, track, and analyze significant events in real-time video streams, acting as a high-performance pre-filter to more expensive AI analysis systems.

This crate was specifically designed to serve as the vision capability filter for the Corpus AI Companion project.

Key Features

  • Temporal Analysis: Uses a multi-channel statistical model to learn "normal" environmental behavior and detect anomalous changes.
  • Spatial Grouping: Implements a "Heatmap Peak-Finding and Region Growing" algorithm to identify coherent objects in motion.
  • Behavioral Analysis: Includes a robust object tracker that adds object permanence, tracking events over time to form complete "Moments."
  • High-Level API: Provides a simple, powerful VisionPipeline API for easy integration.
  • Tunable: All key sensitivity thresholds are exposed in a PipelineConfig struct.

Integration

For detailed instructions on how to integrate this crate into your project, please see the INTEGRATION_GUIDE.md.

License

This project is licensed under the MIT License.