Artur Mukhamadiev
14ae0a901f
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- report valid coverage and depth percentiles even when XYZ ground truth is absent - accept depth bounds and optional color-mapped PNG output for visual inspection - retain accuracy metrics when point_cloud.obj is available - add a batch helper that renders Markdown tables and optional JSON and PNG artifacts - document benchmark inputs, dataset limits, and visualization tradeoffs
84 lines
3.1 KiB
Python
Executable File
84 lines
3.1 KiB
Python
Executable File
#!/usr/bin/env python3
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"""Run scared_dataset_benchmark over many keyframes and print a Markdown table.
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Usage:
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scripts/scared_overview.py [--bench PATH] [--disparities N] [--png-dir DIR]
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[--json-dir DIR] [--depth-range MIN_M MAX_M]
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KEYFRAME_DIR...
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Each KEYFRAME_DIR must hold Left_Image.png, Right_Image.png and
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endoscope_calibration.yaml. Accuracy columns are filled in only for keyframes
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that also contain point_cloud.obj.
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"""
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import argparse
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import json
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import os
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import subprocess
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import sys
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def run(bench, kf, disparities, png_dir, json_dir, depth_range):
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label = "/".join(kf.rstrip("/").split("/")[-2:])
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cmd = [bench, kf, str(disparities)]
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if png_dir:
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os.makedirs(png_dir, exist_ok=True)
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cmd.append(os.path.join(png_dir, label.replace("/", "_") + ".png"))
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else:
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cmd.append("-")
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if depth_range:
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cmd += [str(depth_range[0]), str(depth_range[1])]
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proc = subprocess.run(cmd, capture_output=True, text=True)
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if proc.returncode != 0:
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print(f"{label}: benchmark failed\n{proc.stderr}", file=sys.stderr)
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return label, None
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result = json.loads(proc.stdout)
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if json_dir:
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os.makedirs(json_dir, exist_ok=True)
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with open(os.path.join(json_dir, label.replace("/", "_") + ".json"), "w") as f:
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json.dump(result, f, indent=2)
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return label, result
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def fmt_mm(v):
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return "" if v is None else f"{v * 1000:.2f}"
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def fmt_pct(v):
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return "" if v is None else f"{v * 100:.1f}"
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def main():
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ap = argparse.ArgumentParser()
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ap.add_argument("--bench", default="build-opencv/src/cloud_point/scared_dataset_benchmark")
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ap.add_argument("--disparities", type=int, default=160)
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ap.add_argument("--png-dir")
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ap.add_argument("--json-dir")
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ap.add_argument("--depth-range", nargs=2, type=float, metavar=("MIN_M", "MAX_M"),
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help="depth filter in metres (default: builder defaults 0.01..10)")
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ap.add_argument("keyframes", nargs="+")
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args = ap.parse_args()
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rows = [run(args.bench, kf, args.disparities, args.png_dir, args.json_dir,
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args.depth_range)
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for kf in args.keyframes]
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print("| keyframe | valid % | z p5 / median / p95 (mm) | match ms | GT | coverage % | MAE3D mm | RMSE3D mm | median mm | <1 mm % | <2 mm % | <5 mm % |")
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print("|---|---|---|---|---|---|---|---|---|---|---|---|")
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for label, r in rows:
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if r is None:
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print(f"| {label} | failed | | | | | | | | | | |")
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continue
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z = f"{r['z_p05_m']*1000:.0f} / {r['z_median_m']*1000:.0f} / {r['z_p95_m']*1000:.0f}"
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gt = r.get("has_ground_truth", False)
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print("| {} | {} | {} | {:.0f} | {} | {} | {} | {} | {} | {} | {} | {} |".format(
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label, fmt_pct(r["valid_fraction"]), z, r["matching_ms"],
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"yes" if gt else "no",
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fmt_pct(r.get("coverage")), fmt_mm(r.get("mae_3d_m")),
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fmt_mm(r.get("rmse_3d_m")), fmt_mm(r.get("median_3d_m")),
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fmt_pct(r.get("within_1mm")), fmt_pct(r.get("within_2mm")),
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fmt_pct(r.get("within_5mm"))))
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if __name__ == "__main__":
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main()
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