license: agpl-3.0
tags:
- object-detection
- yolo
- yolo11
- onnx
- ultralytics
- computer-vision
pipeline_tag: object-detection
LunchSpot YOLO11n (ONNX)
This repository hosts an unmodified ONNX export of Ultralytics' YOLO11n (nano) checkpoint, pretrained on COCO. It is not a custom-trained or fine-tuned model — the weights and detection classes are exactly the official Ultralytics release. This repo exists purely as a deployment artifact for the LunchSpot project, so the app can pull the model file at build/deploy time instead of committing a ~10 MB binary to the application repository.
If you need the model for a different purpose, prefer the official
Ultralytics release (GitHub / PyPI ultralytics package) over this mirror.
Credits & license
- Original model: Ultralytics YOLO11
- License: AGPL-3.0, inherited unchanged from Ultralytics' pretrained weights. Any use of this file is subject to that license (or an Ultralytics Enterprise license if you have one).
- No weights were modified. Only the export format changed (PyTorch → ONNX).
What this model does
Standard YOLO11n object detector over the 80 COCO classes, exported to ONNX for CPU inference via ONNX Runtime. LunchSpot uses it as-is and, at the application layer, filters detections down to two COCO classes:
| COCO class | Used for |
|---|---|
person |
occupancy / people counting |