This commit marks the completion of the Iteration 13 'Golden Mix' calibration.
- intel/: Structured documentation into /radar, /scenarios, and /internal subfolders.
- Shenron_debug.md: Comprehensive history of all 13 calibration iterations.
- radar_processor.py: Implemented Blackman-Harris windowing for sidelobe suppression.
- lidar.py: Applied -2.0m parallax shift and ground suppression filtering.
- Sceneset.py: Calibrated specular thresholds and material roughness for stability.
This commit introduces a Flask-based web dashboard for the BATL CARLA orchestrator
and hardens the underlying data processing pipeline to support real-time UI tracking.
Dashboard & GUI:
- Added `dashboard/` directory containing the Flask backend (`app.py`), HTML UI,
and static assets (CSS/JS) for a seamless browser-based simulation controller.
- Created `dashboard.bat` to launch the web dashboard environment.
Pipeline Stability (Unbuffered Streaming):
- `run.bat`: Forced `PYTHONUNBUFFERED=1` to ensure subprocess stdout/stderr
is immediately available.
- `dashboard/app.py`: Injected the unbuffered environment flag into `subprocess.Popen`
to prevent the UI console from freezing during heavy post-processing tasks.
- `src/recorder.py` & `data_to_mcap.py`: Appended `flush=True` to stdout prints
to guarantee immediate log propagation to the web dashboard text stream.
Foxglove Data Integrity:
- `data_to_mcap.py`: Hardened internal JSON schemas (`foxglove.Pose`,
`foxglove.CompressedImage`, `foxglove.PointCloud`) by adding `$schema`, `$id`,
and `title` metadata tags over draft-2020-12. This prevents Foxglove Studio from
attempting internet CDN lookups, fully resolving the "Unable to parse ok response
body as json" crashes when importing local MCAP sets.
RUSHIL AMBARISH KADU