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Download README.md from bubblesmal/spotter-models: direct link, hf CLI and curl.
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https://huggingface.co/bubblesmal/spotter-models/resolve/main/README.md
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hf download hf://bubblesmal/spotter-models/README.md
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2.43 kB
metadata
license: agpl-3.0
library_name: coreml
tags:
- pose-estimation
- keypoint-detection
- fitness
- coreml
- onnx
base_model: Ultralytics/YOLOv8
Spotter models
Models for Spotter, a quiet AI spotter for new gym-goers and people returning from injury
(Knight Hacks IX). The iPhone app runs the pose model on-device; the form model scores reps.
The app reads manifest.json on launch and downloads any model that changed.
Manifest version 2, published 2026-10-10T17:03:35+00:00.
| Model | Format | Path | Size |
|---|---|---|---|
form-quality-label-onnx |
onnx | form/form_quality_label.onnx |
0.9 MB |
form-quality-score-onnx |
onnx | form/form_quality_score.onnx |
0.2 MB |
pose-256-coreml |
coreml | pose/yolov8n-pose-256.mlpackage |
6.7 MB |
pose-320-coreml |
coreml | pose/yolov8n-pose-320.mlpackage |
6.7 MB |
pose-320-onnx |
onnx | pose/yolov8n-pose-320.onnx |
13.3 MB |
Pose: YOLOv8n-pose
- Ultralytics YOLOv8n-pose (COCO keypoints), exported at 320 and 256 px to Core ML (FP16, no NMS) and at 320 px to ONNX.
- Output: one tensor
[1, 56, N]of raw candidates: 4 box values, person confidence, then 17 joints x (x, y, visibility), with sigmoid already applied. Decoding and orientation rules:docs/pose/how-it-works.mdanddocs/pose/pose-result-contract.mdin the Spotter repo. - Video never leaves the phone; only joint positions are sent to the cloud.
Form quality
spotter.ml.form_qualityversion 4 from Databricks Unity Catalog, as two ONNX graphs:label(clean, partial_range, knees_in, forward_lean, fast_lowering, other) andscore(quality, clip to 0-1).- Inputs, one row per rep:
exercise_id,range_deg,weight_kg.exercise_idis a string; unseen exercises are ignored. Numeric inputs may be missing (NaN). - Held-out metrics: label_accuracy 0.188, label_macro_f1 0.2427, quality_mae 0.0807, quality_r2 0.153, test_lifters 40.0, test_reps 35816.0.
- Limitations: a baseline gradient-boosted model trained on labels derived from the phone's rule flags and synthetic sessions, not hand-labelled clips. Expect it to be replaced.
Intended use
Real-time rep counting and form feedback for recreational lifting. Not a medical device and not for diagnosing injuries.
License
The pose model is derived from Ultralytics YOLOv8 and is released under AGPL-3.0, the license of the original weights.