refactor(cli): extract depth postprocess and add tests

- Extract apply_depth_verify_refine_postprocess() from main() for testability
- Add test_depth_cli_postprocess.py using mocks to validate JSON and CSV behavior
- Keeps CLI behavior unchanged
This commit is contained in:
2026-02-05 05:07:48 +00:00
parent 15337d2d15
commit 553cc457f0
2 changed files with 321 additions and 113 deletions
+137 -113
View File
@@ -1,6 +1,7 @@
import click
import cv2
import json
import csv
import numpy as np
import pyzed.sl as sl
from pathlib import Path
@@ -21,6 +22,132 @@ from aruco.depth_verify import verify_extrinsics_with_depth
from aruco.depth_refine import refine_extrinsics_with_depth
def apply_depth_verify_refine_postprocess(
results: Dict[str, Any],
verification_frames: Dict[str, Any],
marker_geometry: Dict[int, Any],
camera_matrices: Dict[str, Any],
verify_depth: bool,
refine_depth: bool,
depth_confidence_threshold: int,
report_csv_path: Optional[str] = None,
) -> Tuple[Dict[str, Any], List[List[Any]]]:
"""
Apply depth verification and refinement to computed extrinsics.
Returns updated results and list of CSV rows.
"""
csv_rows: List[List[Any]] = []
if not (verify_depth or refine_depth):
return results, csv_rows
click.echo("\nRunning depth verification/refinement on computed extrinsics...")
for serial, vf in verification_frames.items():
if str(serial) not in results:
continue
frame = vf["frame"]
ids = vf["ids"]
# Use the FINAL COMPUTED POSE for verification
pose_str = results[str(serial)]["pose"]
T_mean = np.fromstring(pose_str, sep=" ").reshape(4, 4)
cam_matrix = camera_matrices[serial]
marker_corners_world = {
int(mid): marker_geometry[int(mid)]
for mid in ids.flatten()
if int(mid) in marker_geometry
}
if marker_corners_world and frame.depth_map is not None:
verify_res = verify_extrinsics_with_depth(
T_mean,
marker_corners_world,
frame.depth_map,
cam_matrix,
confidence_map=frame.confidence_map,
confidence_thresh=depth_confidence_threshold,
)
results[str(serial)]["depth_verify"] = {
"rmse": verify_res.rmse,
"mean_abs": verify_res.mean_abs,
"median": verify_res.median,
"depth_normalized_rmse": verify_res.depth_normalized_rmse,
"n_valid": verify_res.n_valid,
"n_total": verify_res.n_total,
}
click.echo(
f"Camera {serial} verification: RMSE={verify_res.rmse:.3f}m, "
f"Valid={verify_res.n_valid}/{verify_res.n_total}"
)
if refine_depth:
if verify_res.n_valid < 4:
click.echo(
f"Camera {serial}: Not enough valid depth points for refinement ({verify_res.n_valid}). Skipping."
)
else:
click.echo(f"Camera {serial}: Refining extrinsics with depth...")
T_refined, refine_stats = refine_extrinsics_with_depth(
T_mean,
marker_corners_world,
frame.depth_map,
cam_matrix,
)
verify_res_post = verify_extrinsics_with_depth(
T_refined,
marker_corners_world,
frame.depth_map,
cam_matrix,
confidence_map=frame.confidence_map,
confidence_thresh=depth_confidence_threshold,
)
pose_str_refined = " ".join(f"{x:.6f}" for x in T_refined.flatten())
results[str(serial)]["pose"] = pose_str_refined
results[str(serial)]["refine_depth"] = refine_stats
results[str(serial)]["depth_verify_post"] = {
"rmse": verify_res_post.rmse,
"mean_abs": verify_res_post.mean_abs,
"median": verify_res_post.median,
"depth_normalized_rmse": verify_res_post.depth_normalized_rmse,
"n_valid": verify_res_post.n_valid,
"n_total": verify_res_post.n_total,
}
improvement = verify_res.rmse - verify_res_post.rmse
results[str(serial)]["refine_depth"]["improvement_rmse"] = (
improvement
)
click.echo(
f"Camera {serial} refined: RMSE={verify_res_post.rmse:.3f}m "
f"(Improved by {improvement:.3f}m). "
f"Delta Rot={refine_stats['delta_rotation_deg']:.2f}deg, "
f"Trans={refine_stats['delta_translation_norm_m']:.3f}m"
)
verify_res = verify_res_post
if report_csv_path:
for mid, cidx, resid in verify_res.residuals:
csv_rows.append([serial, mid, cidx, resid])
if report_csv_path and csv_rows:
with open(report_csv_path, "w", newline="") as f:
writer = csv.writer(f)
writer.writerow(["serial", "marker_id", "corner_idx", "residual"])
writer.writerows(csv_rows)
click.echo(f"Saved depth verification report to {report_csv_path}")
return results, csv_rows
@click.command()
@click.option("--svo", "-s", multiple=True, required=False, help="Path to SVO files.")
@click.option("--markers", "-m", required=True, help="Path to markers parquet file.")
@@ -260,119 +387,16 @@ def main(
return
# 4. Run Depth Verification if requested
csv_rows: List[List[Any]] = []
if verify_depth or refine_depth:
click.echo("\nRunning depth verification/refinement on computed extrinsics...")
for serial, acc in accumulators.items():
if serial not in verification_frames or str(serial) not in results:
continue
# Retrieve stored frame data
vf = verification_frames[serial]
frame = vf["frame"]
ids = vf["ids"]
# Use the FINAL COMPUTED POSE for verification
pose_str = results[str(serial)]["pose"]
T_mean = np.fromstring(pose_str, sep=" ").reshape(4, 4)
cam_matrix = camera_matrices[serial]
marker_corners_world = {
int(mid): marker_geometry[int(mid)]
for mid in ids.flatten()
if int(mid) in marker_geometry
}
if marker_corners_world and frame.depth_map is not None:
verify_res = verify_extrinsics_with_depth(
T_mean,
marker_corners_world,
frame.depth_map,
cam_matrix,
confidence_map=frame.confidence_map,
confidence_thresh=depth_confidence_threshold,
)
results[str(serial)]["depth_verify"] = {
"rmse": verify_res.rmse,
"mean_abs": verify_res.mean_abs,
"median": verify_res.median,
"depth_normalized_rmse": verify_res.depth_normalized_rmse,
"n_valid": verify_res.n_valid,
"n_total": verify_res.n_total,
}
click.echo(
f"Camera {serial} verification: RMSE={verify_res.rmse:.3f}m, "
f"Valid={verify_res.n_valid}/{verify_res.n_total}"
)
if refine_depth:
if verify_res.n_valid < 4:
click.echo(
f"Camera {serial}: Not enough valid depth points for refinement ({verify_res.n_valid}). Skipping."
)
else:
click.echo(
f"Camera {serial}: Refining extrinsics with depth..."
)
T_refined, refine_stats = refine_extrinsics_with_depth(
T_mean,
marker_corners_world,
frame.depth_map,
cam_matrix,
)
verify_res_post = verify_extrinsics_with_depth(
T_refined,
marker_corners_world,
frame.depth_map,
cam_matrix,
confidence_map=frame.confidence_map,
confidence_thresh=depth_confidence_threshold,
)
pose_str_refined = " ".join(
f"{x:.6f}" for x in T_refined.flatten()
)
results[str(serial)]["pose"] = pose_str_refined
results[str(serial)]["refine_depth"] = refine_stats
results[str(serial)]["depth_verify_post"] = {
"rmse": verify_res_post.rmse,
"mean_abs": verify_res_post.mean_abs,
"median": verify_res_post.median,
"depth_normalized_rmse": verify_res_post.depth_normalized_rmse,
"n_valid": verify_res_post.n_valid,
"n_total": verify_res_post.n_total,
}
improvement = verify_res.rmse - verify_res_post.rmse
results[str(serial)]["refine_depth"]["improvement_rmse"] = (
improvement
)
click.echo(
f"Camera {serial} refined: RMSE={verify_res_post.rmse:.3f}m "
f"(Improved by {improvement:.3f}m). "
f"Delta Rot={refine_stats['delta_rotation_deg']:.2f}deg, "
f"Trans={refine_stats['delta_translation_norm_m']:.3f}m"
)
verify_res = verify_res_post
if report_csv:
for mid, cidx, resid in verify_res.residuals:
csv_rows.append([serial, mid, cidx, resid])
# 5. Save CSV Report
if report_csv and csv_rows:
import csv
with open(report_csv, "w", newline="") as f:
writer = csv.writer(f)
writer.writerow(["serial", "marker_id", "corner_idx", "residual"])
writer.writerows(csv_rows)
click.echo(f"Saved depth verification report to {report_csv}")
apply_depth_verify_refine_postprocess(
results,
verification_frames,
marker_geometry,
camera_matrices,
verify_depth,
refine_depth,
depth_confidence_threshold,
report_csv,
)
# 6. Save to JSON
with open(output, "w") as f: