# ZeroLeft

- **Event:** [Meta Global AI Developer Hackathon](https://cerebralvalley.ai/e/meta-ai-developer-hackathon)
- **When:** Oct 26, 12:00 PM – Nov 4, 9:00 PM (EST)
- **Where:** Online
- **Team:** [Gustavo Adolfo Murillo Gutierrez](https://cerebralvalley.ai/u/Murillo)
- **GitHub:** https://github.com/MurilloLog/ZeroLeft
- **Demo video:** https://youtu.be/ze_SFyxsAlk
- **Gallery:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/593

Surgical instrument traceability remains a critical challenge in modern healthcare, where counting, identification, and verification still rely on manual workflows. A nurse can track up to 1,500 instruments a day. In real ORs, this process fails due to specular reflections on metal materials, occlusions, blood, overlapping tools, and visually similar geometries.

ZeroLeft is an experimental framework I built from scratch during this hackathon to automatically audit PRE- and POST-surgical trays and explore the real capabilities and limitations of Meta's foundation models. It operates under four modes:
1) Manual click segmentation with local SAM,
2) Text-prompt segmentation with SAM 3.1 API,
3) Automatic mask proposal with background filtering, and
4) Agentic exemplar-based comparison where SAM proposes shapes and Muse Spark classifies by comparing dirty crops to clean white-background exemplars.

The goal is to provide a reproducible stress-test and benchmark showing where SAM 3.1 returns 0 boxes for fine-grained terms, where closed-set bias occurs, and what architecture (proposer + exemplar comparator) is needed to move toward zero-left error. Every run exports a JSON audit trail, quantitative evaluation, and WHO surgical checklist.

## More from Meta Global AI Developer Hackathon

- [Blackout](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/590)
- [Meta IntentLoop](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/591)
- [athlete2humanoid](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/592)
- [Veil Privacy](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/594)
- [Tripwire](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/595)
- [Traction Radar](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/596)

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