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docs: reorder README sections — v0.7.0 first, then descending

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Co-Authored-By: claude-flow <ruv@ruv.net>
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@ -96,6 +96,49 @@ node scripts/mincut-person-counter.js --port 5006 # Correct person counting
>
---
### What's New in v0.7.0
<details open>
<summary><strong>Camera Ground-Truth Training — 92.9% PCK@20</strong></summary>
**v0.7.0 adds camera-supervised pose training** using MediaPipe + real ESP32 CSI data:
| Capability | What it does | ADR |
|-----------|-------------|-----|
| **Camera ground-truth collection** | MediaPipe PoseLandmarker captures 17 COCO keypoints at 30fps, synced with ESP32 CSI | [ADR-079](docs/adr/ADR-079-camera-ground-truth-training.md) |
| **ruvector subcarrier selection** | Variance-based top-K reduces input by 50% (70→35 subcarriers) | ADR-079 O6 |
| **Stoer-Wagner min-cut** | Person-specific subcarrier cluster separation for multi-person training | ADR-079 O8 |
| **Scalable WiFlow model** | 4 presets: lite (189K) → small (474K) → medium (800K) → full (7.7M params) | ADR-079 |
```bash
# Collect ground truth (camera + ESP32 simultaneously)
python scripts/collect-ground-truth.py --duration 300 --preview
python scripts/record-csi-udp.py --duration 300
# Align CSI windows with camera keypoints
node scripts/align-ground-truth.js --gt data/ground-truth/*.jsonl --csi data/recordings/*.csi.jsonl
# Train WiFlow model (start lite, scale up as data grows)
node scripts/train-wiflow-supervised.js --data data/paired/*.jsonl --scale lite
# Evaluate
node scripts/eval-wiflow.js --model models/wiflow-real/wiflow-v1.json --data data/paired/*.jsonl
```
**Result: 92.9% PCK@20** from a 5-minute data collection session with one ESP32-S3 and one webcam.
| Metric | Before (proxy) | After (camera-supervised) |
|--------|----------------|--------------------------|
| PCK@20 | 0% | **92.9%** |
| Eval loss | 0.700 | **0.082** |
| Bone constraint | N/A | **0.008** |
| Training time | N/A | **19 minutes** |
| Model size | N/A | **974 KB** |
Pre-trained model: [HuggingFace ruv/ruview/wiflow-v1](https://huggingface.co/ruv/ruview)
</details>
### Pre-Trained Models (v0.6.0) — No Training Required
<details open>
@ -175,49 +218,6 @@ All scripts support `--replay data/recordings/*.csi.jsonl` for offline analysis
</details>
### What's New in v0.7.0
<details open>
<summary><strong>Camera Ground-Truth Training — 92.9% PCK@20</strong></summary>
**v0.7.0 adds camera-supervised pose training** using MediaPipe + real ESP32 CSI data:
| Capability | What it does | ADR |
|-----------|-------------|-----|
| **Camera ground-truth collection** | MediaPipe PoseLandmarker captures 17 COCO keypoints at 30fps, synced with ESP32 CSI | [ADR-079](docs/adr/ADR-079-camera-ground-truth-training.md) |
| **ruvector subcarrier selection** | Variance-based top-K reduces input by 50% (70→35 subcarriers) | ADR-079 O6 |
| **Stoer-Wagner min-cut** | Person-specific subcarrier cluster separation for multi-person training | ADR-079 O8 |
| **Scalable WiFlow model** | 4 presets: lite (189K) → small (474K) → medium (800K) → full (7.7M params) | ADR-079 |
```bash
# Collect ground truth (camera + ESP32 simultaneously)
python scripts/collect-ground-truth.py --duration 300 --preview
python scripts/record-csi-udp.py --duration 300
# Align CSI windows with camera keypoints
node scripts/align-ground-truth.js --gt data/ground-truth/*.jsonl --csi data/recordings/*.csi.jsonl
# Train WiFlow model (start lite, scale up as data grows)
node scripts/train-wiflow-supervised.js --data data/paired/*.jsonl --scale lite
# Evaluate
node scripts/eval-wiflow.js --model models/wiflow-real/wiflow-v1.json --data data/paired/*.jsonl
```
**Result: 92.9% PCK@20** from a 5-minute data collection session with one ESP32-S3 and one webcam.
| Metric | Before (proxy) | After (camera-supervised) |
|--------|----------------|--------------------------|
| PCK@20 | 0% | **92.9%** |
| Eval loss | 0.700 | **0.082** |
| Bone constraint | N/A | **0.008** |
| Training time | N/A | **19 minutes** |
| Model size | N/A | **974 KB** |
Pre-trained model: [HuggingFace ruv/ruview/wiflow-v1](https://huggingface.co/ruv/ruview)
</details>
### What's New in v0.5.5
<details>