lipan
cec0766e67
- 算法包替换为 delivery_v1.2（coupler_panel 新增 autotune/layer_select，underframe_deflection 新增 single_beam 管线），删除 delivery_v1.1 - manifests/adapters 的 PYTHONPATH 与版本说明同步更新到 v1.2 - 新增任务级 CAD 文件支持（task_cad_files 表、上传/读取路由、TaskManager 全选与加载显示） - 新增 train-measurement 自定义前端面板（YAML 编辑器 + 可视化 ROI 配置 + 3D 取点） - PointCloudViewer 支持 PLY 叠加层渲染与 ROI 拾取 - Dockerfile 改用 Miniforge 安装 pythonocc-core，修复 libgomp/libstdc++ 依赖
114 lines
4.7 KiB
Python
114 lines
4.7 KiB
Python
"""Integration entry point — the contract for the software integrator.
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Three input files, one Excel output:
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--roi ROI JSON (6-key AABB crop hyper-parameters, in the cloud frame)
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--cloud full-vehicle point cloud PLY (may be multi-GB; cropped by streaming)
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--stp theoretical CAD STEP file (recorded for audit/traceability)
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--out output directory (gets eval_report.xlsx + intermediates)
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The cloud is cropped to the ROI inside the algorithm (no external
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pre-processing needed), the coupler panel is measured, and the two
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deflection angles + intermediate values are written to an .xlsx report.
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Example::
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python examples/run_integration.py \
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--roi examples/roi_train2_coupler.json \
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--cloud E:/BaiduNetdiskDownload/pointsCloud_data/train_2_1T.ply \
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--stp E:/BaiduNetdiskDownload/pointsCloud_data/m000004802418tc01_asm.stp \
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--out runs/train2_integration \
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--profile train2_coupler
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"""
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from __future__ import annotations
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import argparse
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import logging
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import time
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from pathlib import Path
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from coupler_panel.exceptions import CouplerError
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from coupler_panel.pipeline import run_coupler_measurement_pipeline
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from coupler_panel.reporting import build_row_from_summary, write_excel_report
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from coupler_panel.roi_select import load_roi_json
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def _build_parser() -> argparse.ArgumentParser:
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p = argparse.ArgumentParser(description=__doc__)
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p.add_argument("--roi", type=Path, required=True, help="ROI JSON (6-key AABB).")
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p.add_argument("--cloud", type=Path, required=True, help="Full-vehicle point cloud PLY.")
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p.add_argument("--stp", type=Path, default=None, help="Theoretical CAD STEP (audit).")
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p.add_argument("--out", type=Path, required=True, help="Output directory.")
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p.add_argument("--profile", type=str, default="train2_coupler",
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help="Config profile (default: train2_coupler).")
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p.add_argument("--config", type=Path, default=None, help="Optional YAML override.")
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p.add_argument("--gt-theta-right", type=float, default=0.0,
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help="Known/expected theta_right (deg) for the error column. Default 0.")
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p.add_argument("--gt-theta-ref", type=float, default=0.0,
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help="Known/expected theta_ref (deg) for the error column. Default 0.")
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p.add_argument("--sample-id", type=str, default=None, help="Row label in the report.")
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return p
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def main(argv: list[str] | None = None) -> int:
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logging.basicConfig(level=logging.INFO, format="%(levelname)s %(name)s: %(message)s")
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log = logging.getLogger("run_integration")
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args = _build_parser().parse_args(argv)
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roi_spec = load_roi_json(args.roi)
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log.info("ROI bbox: x[%g,%g] y[%g,%g] z[%g,%g]",
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roi_spec.x_min, roi_spec.x_max, roi_spec.y_min,
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roi_spec.y_max, roi_spec.z_min, roi_spec.z_max)
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log.info("cloud: %s", args.cloud)
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log.info("stp (audit): %s", args.stp)
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sample_id = args.sample_id or args.cloud.stem
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t0 = time.perf_counter()
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try:
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result = run_coupler_measurement_pipeline(
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input_cloud=args.cloud,
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out_dir=args.out,
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config_path=args.config,
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profile=args.profile,
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roi_spec=roi_spec,
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progress=lambda s, f: log.info("[%5.1f%%] %s", f * 100, s),
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)
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except CouplerError as exc:
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log.error("measurement failed: %s", exc)
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return 2
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pipeline_seconds = time.perf_counter() - t0
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# n_points after ROI crop is recorded in <out>/roi.json diagnostics.
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import json as _json
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roi_diag = _json.loads((args.out / "roi.json").read_text(encoding="utf-8"))
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n_roi = int(roi_diag.get("diagnostics", {}).get("n_out", 0))
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n_in = int(roi_diag.get("diagnostics", {}).get("n_in", n_roi))
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row = build_row_from_summary(
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sample_id=sample_id,
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ply_path=str(args.cloud),
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roi_kind=f"aabb {roi_spec.x_min:.0f}-{roi_spec.x_max:.0f},"
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f"{roi_spec.y_min:.0f}-{roi_spec.y_max:.0f},"
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f"{roi_spec.z_min:.0f}-{roi_spec.z_max:.0f}",
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measured=result.to_dict(),
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gt_angles=(args.gt_theta_right, args.gt_theta_ref),
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registration=None,
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n_points_in=n_in,
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n_points_after_roi=n_roi,
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pipeline_seconds=pipeline_seconds,
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)
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# Record the STP path in the row's extra metadata (audit trail).
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row.extra["stp_audit_path"] = str(args.stp) if args.stp else ""
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xlsx = write_excel_report([row], args.out / "eval_report.xlsx")
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log.info("theta_right=%+.4f theta_ref=%+.4f flags=%s",
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result.theta_right_deg, result.theta_ref_deg, result.quality_flags)
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log.info("wrote %s", xlsx)
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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