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Update README + user-guide for PR #405 review-fix additions

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- serve now uses --bind 127.0.0.1:9880 (loopback default) instead of --port
- Add fingerprint subcommand to CLI tables
- Document RUVIEW_BRAIN_URL env var + --brain flag
- Flag pose path as amplitude-energy heuristic stub (not trained WiFlow)
- Security note on exposing server outside loopback
- Add wifi-densepose-pointcloud + wifi-densepose-geo rows to crate table

Co-Authored-By: claude-flow <ruv@ruv.net>
This commit is contained in:
ruv
2026-04-20 12:48:45 -04:00
parent e1843c047e
commit 0824de7665
2 changed files with 25 additions and 13 deletions
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docs/user-guide.md
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@@ -547,12 +547,16 @@ RuView can generate real-time 3D point clouds by fusing camera depth estimation
cd rust-port/wifi-densepose-rs
cargo build --release -p wifi-densepose-pointcloud
# Start the server (auto-detects camera + CSI)
./target/release/ruview-pointcloud serve --port 9880
# Start the server (auto-detects camera + CSI). Loopback-only by default.
./target/release/ruview-pointcloud serve --bind 127.0.0.1:9880
```
Open `http://localhost:9880` for the interactive Three.js 3D viewer.
> **Security note.** The server exposes live camera, skeleton, vitals, and occupancy over HTTP. The `--bind` flag defaults to `127.0.0.1:9880` (loopback-only). Exposing on `0.0.0.0` or a LAN IP is opt-in — the server logs a warning when it does, but there is no auth/TLS layer. Put a reverse proxy in front if you need remote access.
> **Brain URL.** Observations are POSTed to `http://127.0.0.1:9876` by default. Override via the `RUVIEW_BRAIN_URL` environment variable or the `--brain <url>` flag on `serve` / `train`.
### Sensors
| Sensor | Auto-detected | Data |
@@ -565,17 +569,18 @@ Open `http://localhost:9880` for the interactive Three.js 3D viewer.
| Command | Description |
|---------|-------------|
| `ruview-pointcloud serve --port 9880` | Start HTTP server + Three.js viewer |
| `ruview-pointcloud serve --bind 127.0.0.1:9880` | Start HTTP server + Three.js viewer (loopback-only by default) |
| `ruview-pointcloud demo` | Generate synthetic point cloud (no hardware needed) |
| `ruview-pointcloud capture --output room.ply` | Capture single frame to PLY file |
| `ruview-pointcloud cameras` | List available cameras |
| `ruview-pointcloud train --data-dir ./data` | Depth calibration + occupancy training |
| `ruview-pointcloud train --data-dir ./data [--brain URL]` | Depth calibration + occupancy training (writes under canonicalized `data-dir`; refuses `..` traversal) |
| `ruview-pointcloud csi-test --count 100` | Send test CSI frames (no ESP32 needed) |
| `ruview-pointcloud fingerprint <name> [--seconds 5]` | Record a named CSI room fingerprint for later matching |
### Pipeline Components
1. **ADR-018 Parser** — Decodes ESP32 CSI binary frames from UDP, extracts I/Q subcarrier amplitudes and phases
2. **WiFlow Pose** — 17 COCO keypoint estimation from CSI (loads `wiflow-v1.json`, 186K params)
1. **ADR-018 Parser** — Decodes ESP32 CSI binary frames from UDP (magic `0xC5110001` raw CSI and `0xC5110006` feature state), extracts I/Q subcarrier amplitudes and phases. Lives in `parser.rs`; unit-tested against hand-rolled test vectors.
2. **Pose (stub)** — 17 COCO keypoint *layout* generated by `heuristic_pose_from_amplitude` from CSI amplitude energy. This is **not** the trained WiFlow model — it is a placeholder so the viewer has a skeleton to render. Wiring to real Candle/ONNX inference from the `wifi-densepose-nn` crate is a planned follow-up.
3. **Vital Signs** — Breathing rate from CSI phase analysis (peak counting on stable subcarrier)
4. **Motion Detection** — CSI amplitude variance over 20 frames, triggers adaptive capture
5. **RF Tomography** — Backprojection from per-node RSSI to 8×8×4 occupancy grid