| --- |
| license: other |
| library_name: scikit-learn |
| tags: |
| - pose-estimation |
| - exercise-recognition |
| - video-classification |
| - pozify |
| datasets: |
| - RickyRiccio/Real_Time_Exercise_Recognition_Dataset |
| --- |
| |
| # Pozify Exercise Router |
|
|
| This repository contains the Pozify exercise-router artifacts for classifying pose windows as |
| `squat`, `push_up`, `shoulder_press`, or `unknown`. |
|
|
| ## Model Details |
|
|
| The active artifact is selected by `router_selection.json`. |
|
|
| Current selected artifact: |
|
|
| ```json |
| { |
| "selected_model": "temporal.pt", |
| "selected_artifact": "temporal.pt", |
| "reason": "prefer BiLSTM temporal when available; baseline falls back when temporal is missing" |
| } |
| ``` |
|
|
| Artifacts: |
|
|
| - `temporal.pt`: selected PyTorch BiLSTM temporal model trained over 30-frame feature tensors. |
| - `router_selection.json`: active artifact selector used by Pozify runtime loading. |
| - `router.joblib`: scikit-learn baseline artifact kept for comparison and fallback. |
| - `training_report.md`: training and evaluation metrics. |
|
|
| ## Intended Use |
|
|
| The router is intended for Pozify's local app pipeline. It routes normalized pose sequences to the |
| appropriate exercise-specific analyzer or rejects unsupported/uncertain clips as `unknown`. |
|
|
| Supported labels: |
|
|
| - `squat` |
| - `push_up` |
| - `shoulder_press` |
| - `unknown` |
|
|
| ## Training Data |
|
|
| Primary source: |
|
|
| - `RickyRiccio/Real_Time_Exercise_Recognition_Dataset` |
|
|
| Unsupported classes from the source dataset, including curl variations, are mapped to `unknown`. |
| Custom unknown clips can include idle standing, setup motion, stretching, partial reps, severe |
| occlusion, and bad camera angles. |
|
|
| ## Features |
|
|
| The router uses 30-frame sliding windows with engineered pose features: |
|
|
| - normalized landmarks |
| - landmark visibility |
| - knee, hip, elbow, and shoulder angles |
| - relative distances such as hand width over shoulder width |
| - frame deltas and velocities |
|
|
| ## Evaluation |
|
|
| The latest training report is included as `training_report.md`. |
|
|
| Summary: |
|
|
| | Model | Artifact | Accuracy | Unknown rejection rate | |
| | --------------- | ----------------- | -------: | ---------------------: | |
| | Baseline | `baseline.joblib` | 0.9987 | 0.9984 | |
| | BiLSTM temporal | `temporal.pt` | 0.9964 | 0.9984 | |
|
|
| ## Limitations |
|
|
| - Metrics are based on the current router-window cache, not a broad deployment benchmark. |
| - The router expects usable pose extraction and full-body framing where relevant. |
| - Unsupported exercises are intentionally routed to `unknown`. |
| - Additional independent held-out videos are needed before treating this as production-grade. |
|
|
| ## Runtime Loading |
|
|
| Pozify loads this repository by default. Set `POZIFY_ROUTER_HF_REPO_ID` only to override the default |
| with another compatible router repo: |
|
|
| ```bash |
| export POZIFY_ROUTER_HF_REPO_ID=owner/other-pozify-router |
| ``` |
|
|
| For private repositories, authenticate with `hf auth login` or set `HF_TOKEN`. |
|
|
