crosstyan/zed-playground
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

feat(calibration): add data-driven ground alignment with debug and fast iteration flags

Browse Source
This commit is contained in:
crosstyan
2026-02-07 03:20:16 +00:00
parent afc8e9034d
commit 446c02d42a
10 changed files with 1221 additions and 33 deletions
Download Patch File Download Diff File Expand all files Collapse all files
py_workspace/.sisyphus/notepads/ground-plane-alignment/learnings.md
+63
View File
@@ -0,0 +1,63 @@
- Implemented core alignment utilities in aruco/alignment.py.
- Used Rodrigues' rotation formula for vector alignment with explicit handling for parallel and anti-parallel cases.
- Implemented `FACE_MARKER_MAP` and `get_face_normal_from_geometry` to support multi-marker face normal averaging.
- Implemented `detect_ground_face` using dot-product scoring against camera up-vector with `loguru` debug logging.
- Integrated ground-plane alignment into `calibrate_extrinsics.py` with CLI-toggled heuristic and explicit face/marker selection.
## SVO Directory Expansion
- Implemented directory expansion for `--svo` argument.
- Iterates through provided paths, checks if directory, and finds `.svo` and `.svo2` files.
- Maintains backward compatibility for single file paths.
- Sorts found files to ensure deterministic processing order.
## ArUco Dictionary Selection
- Added `--aruco-dictionary` CLI option mapping string names to `cv2.aruco` constants.
- Defaults to `DICT_4X4_50` but supports all standard dictionaries including AprilTags.
- Passed to `create_detector` to allow flexibility for different marker sets.
## Minimum Markers Configuration
- Added `--min-markers` CLI option (default 1).
- Passed to `estimate_pose_from_detections` to filter out poses with insufficient marker support.
- Useful for improving robustness or allowing single-marker poses when necessary.
## Logging Improvements
- Added `loguru` debug logs for:
- Number of detected markers per frame.
- Pose acceptance/rejection with specific reasons (reprojection error, marker count).
## Dynamic Face Mapping
- Implemented `load_face_mapping` in `aruco/marker_geometry.py` to read face definitions from parquet metadata.
- Parquet file must contain `name` (string) and `ids` (list of ints) columns.
- `calibrate_extrinsics.py` now loads this map at runtime and passes it to alignment functions.
- `aruco/alignment.py` functions (`get_face_normal_from_geometry`, `detect_ground_face`) now accept an optional `face_marker_map` argument.
## Strict Data-Driven Alignment
- Removed implicit fallback to `FACE_MARKER_MAP` in `aruco/alignment.py`.
- `calibrate_extrinsics.py` now explicitly checks for loaded face mapping.
- If mapping is missing (e.g., old parquet without `name`/`ids`), alignment is skipped with a warning instead of using hardcoded defaults.
- This enforces the requirement that ground alignment configuration must come from the marker definition file.
- Alignment tests verify that `rotation_align_vectors` correctly handles identity, 90-degree, and anti-parallel cases.
- `detect_ground_face` and `get_face_normal_from_geometry` are now data-driven, requiring an explicit `face_marker_map` at runtime.
- Unit tests use mock geometry to verify normal computation and face selection logic without requiring real SVO/parquet data.
- **Parquet Schema**: The marker configuration parquet file (`standard_box_markers_600mm.parquet`) uses a schema with `name` (string), `ids` (list<int64>), and `corners` (list<list<list<float64>>>).
- **Dual Loading Strategy**: The system loads this single file in two ways:
1. `load_marker_geometry`: Flattens `ids` and `corners` to build a global map of Marker ID -> 3D Corners.
2. `load_face_mapping`: Uses `name` and `ids` to group markers by face (e.g., "bottom"), which is critical for ground plane alignment.
## Runtime Stability
- Fixed `AttributeError: 'FrameData' object has no attribute 'confidence_map'` by explicitly adding it to the dataclass and populating it in `SVOReader`.
- Added `--debug` flag to control log verbosity, defaulting to cleaner INFO level output.
## Consistency Hardening
- Removed "using default fallback" messaging from `calibrate_extrinsics.py` to align with the strict data-driven requirement.
## Fast Iteration
- Added `--max-samples` CLI option to `calibrate_extrinsics.py` to allow processing a limited number of samples (e.g., 1 or 3) instead of the full SVO.
- This significantly speeds up the development loop when testing changes to pose estimation or alignment logic that don't require the full dataset.