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