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doc/README_BodyTracker.md
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doc/README_BodyTracker.md
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# appRobotBodyTrack
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3D-Body-Tracking für Roboter aus Mehrkamera-ArUco-Bildern.
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**Input**
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- Bilder: `render_*.png`
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- Intrinsics: `render_*.npz`
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- Konfiguration: `robot.json`
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**Output**
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- Gelenke **R⁷** → `{x, y, z, a, b, c, e}` (mm / Grad)
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---
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## Interfaces
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Eine Logik, drei Zugänge:
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- **Python**
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- **CLI**
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- **REST (FastAPI)**
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---
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## Quickstart
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### Python
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```python
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from scripts import estimate_from_dir
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result = estimate_from_dir("data/Scene8", robot_json="robot.json")
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print(result.joints)
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print(result.confidence)
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```
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---
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### CLI
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```bash
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pip install -e .
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python -m scripts data/Scene8 --robot robot.json
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python -m scripts data/Scene8 --robot robot.json --cameras a,b,d
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```
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---
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### REST API
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```bash
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docker compose up
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```
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**Request:**
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```python
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import requests
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resp = requests.post(
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"http://localhost:8446/v1/estimate",
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files=[
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("images", ("render_a.png", open("render_a.png", "rb"))),
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("intrinsics", ("render_a.npz", open("render_a.npz", "rb"))),
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],
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)
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print(resp.json()["joints"])
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```
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---
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## API
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| Endpoint | Methode | Zweck |
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|----------|--------|------|
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| `/v1/estimate` | POST | Bilder → Gelenke |
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| `/v1/health` | GET | Status |
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| `/v1/config` | GET | aktive Konfiguration |
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**Response:**
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```json
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{
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"joints": {"x": 50.2, "y": -2.1, "z": 94.8, "a": 20.1},
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"confidence": {"x": "high", "b": "low"},
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"residual_rms": 1.45,
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"n_markers": 56,
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"processing_ms": 1240
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}
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```
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---
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## Struktur
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```
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.
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├── scripts/
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├── config/robot.json
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├── tests/
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└── docker-compose.yaml
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```
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---
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## Deployment (Docker / Portainer)
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**Volume:**
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```yaml
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- /opt/approbot/config/robot.json:/config/robot.json:ro
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```
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**Healthcheck:**
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```bash
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curl http://<host>:8446/v1/health
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```
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---
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## Konfiguration
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Zentrale Datei: **`robot.json`**
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Verwendete Bereiche:
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- `links`
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- `pose_estimation`
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- `vision_config`
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- `movements`
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- `units`
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---
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## Stack (minimal)
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- numpy
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- scipy
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- opencv (aruco)
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- fastapi + uvicorn
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---
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## Naming
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- **BodyTrack** → Tracking (dynamisch) ✅
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- **BodyMap** → Modell / Repräsentation
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- **BodySense** → Wahrnehmung (low-level)
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