# machinefi/trio-retina

<https://repo.masters-masters.com/en/repos/machinefi/trio-retina>

[Home](https://repo.masters-masters.com/en) › [machinefi](https://repo.masters-masters.com/en/owners/machinefi) › [trio-retina](https://repo.masters-masters.com/en/repos/machinefi/trio-retina)

machinefi/trio-retina has 189 stars on GitHub. Its RepoMasters card: Prototype tier. Model-agnostic state layer for world models — turn any detector (YOLO ·…

| Field | Value |
| --- | --- |
| Owner | [machinefi](https://repo.masters-masters.com/en/owners/machinefi) |
| Stars | 189 |
| Forks | 43 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | Apache-2.0 |
| Created | 2026 |
| Topics | computer-vision, edge-ai, event-stream, object-detection, object-tracking, perception, python, rtsp, video-analytics, vlm |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [machinefi/trio-retina](https://github.com/machinefi/trio-retina) |

## Repository

Model-agnostic state layer for world models — turn any detector (YOLO · VLM · DINO) into one standard, queryable stream of events + latent state. numpy-only, runs on CPU at the edge.

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.