# id — Camera identification ROI authoring tool

Interactive utility to author a JSON config that uniquely identifies each
camera by checking fixed ROIs for the presence of ArUco markers. The resulting
`configs/camera_ident.config.json` is used by
`s6.utils.camera_identifier_aruco.CameraIDIdentifierAruco` to reorder images reliably.

## Usage

```bash
# Ensure the stream server is running first (in another terminal)
s6 stream

# Launch the ROI authoring UI
s6 id
# or
python -m s6.app.id
```

## How it works
- Connects to the TCP stream (`s6.utils.streamer.VideoStreamClient`) using
  the host from `ConnectionConfig.load_default().stream_server`.
- Displays one camera view at a time and lets you draw rectangular ROIs via
  mouse. Each ROI can be positive (must contain at least one detected ArUco
  center) or negative (must contain none) depending on a toggle.
- Saves a JSON config with `rule_config` — mapping from camera roles to lists
  of region specs: `{"type": "rect", "bbox": [x1, y1, x2, y2], "negate": bool}`.
  When there are three cameras the default roles are `R`, `B`, and `L`; for
  other counts they are numeric strings (`"0"`, `"1"`, ...).
- At runtime, `CameraIDIdentifierAruco.order(images)` evaluates rules and
  returns a dict `{camera_id: image}`.

## UI controls
- Drag with left mouse button: draw a rectangular ROI for the current role.
- `m`: toggle POSITIVE/NEGATIVE (negated) mode for new ROIs.
- `r`: cycle camera role (`R/B/L` or numeric).
- `d`: cycle which camera view is displayed.
- `c`: clear all ROIs.
- `Enter` or `Space`: finish and write `configs/camera_ident.config.json`.

## Troubleshooting
- Start `s6 stream` first; the tool waits for the first frame to size the UI.
- If you don’t see markers, ensure your OpenCV build includes `cv2.aruco`
  (opencv-contrib) and that markers are visible in the scene.