feat: 升级算法包 delivery_v1.1 → v1.2，新增任务级 CAD 与测距面板
- 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
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"""Generate synthetic test point clouds at varying injected panel-deflection
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angles. Each cloud is produced by the *existing* CAD synthesis path
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(parse → sample → deflect → noise) **with the scanner-pose jitter step
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turned off**, so each PLY already lives in the CAD frame — which is the
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contract the main measurement pipeline expects (no registration step).
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Each PLY is paired with one row in ``manifest.json`` so the batch
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evaluator knows the GT angle to compare against.
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Run::
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python examples/generate_test_clouds.py \
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--stp test_data/lu1.stp \
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--out test_data/synth \
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--profile lu1_af4
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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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from pathlib import Path
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from coupler_panel.config import load_config, resolve_auto
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from coupler_panel.data_prep import parse_cad, synthesize_cloud
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from coupler_panel.io_utils import write_point_cloud, write_json
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# (theta_right_deg, theta_ref_deg) pairs — mirrors the spirit of the
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# existing lu1_deflection_sweep matrix.
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DEFAULT_INJECTIONS = [
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(0.0, 0.0),
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(0.1, 0.0),
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(0.3, 0.0),
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(0.5, 0.0),
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(1.0, 0.0),
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(2.0, 0.0),
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(0.0, 0.5),
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(0.5, 0.5),
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(1.0, 1.0),
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]
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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("--stp", type=Path, required=True, help="Path to the panel STEP file.")
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p.add_argument("--out", type=Path, required=True, help="Output directory for PLYs + manifest.")
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p.add_argument("--profile", type=str, default="lu1_af4", help="Config profile.")
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p.add_argument(
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"--config",
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type=Path,
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default=None,
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help="Optional YAML override; takes precedence over --profile.",
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)
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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("generate_test_clouds")
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args = _build_parser().parse_args(argv)
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cfg = load_config(args.config, profile=args.profile)
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cfg = resolve_auto(cfg)
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log.info("parsing CAD: %s", args.stp)
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parsed = parse_cad(args.stp, cfg["cad"])
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out_dir = args.out
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out_dir.mkdir(parents=True, exist_ok=True)
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# CAD nominal GT — kept as an audit reference (not consumed by the
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# main pipeline, which only needs the STP).
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write_json(parsed.gt.to_dict(), out_dir / "gt.json")
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manifest: list[dict] = []
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for i, (th_r, th_z) in enumerate(DEFAULT_INJECTIONS):
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cfg_i = dict(cfg)
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cfg_i["panel_deflection"] = {
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"enabled": True,
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"theta_right_deg": float(th_r),
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"theta_ref_deg": float(th_z),
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}
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# Scanner-pose jitter is OFF: the cloud must already be in the
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# CAD frame because the main pipeline does not register.
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cfg_i["transform"] = {"enabled": False}
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log.info("[%d/%d] synthesising θ_right=%+.2f° θ_ref=%+.2f°",
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i + 1, len(DEFAULT_INJECTIONS), th_r, th_z)
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synth = synthesize_cloud(
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parsed,
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sampling_cfg=cfg_i["sampling"],
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noise_cfg=cfg_i.get("noise", {}),
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transform_cfg=cfg_i["transform"],
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scan_cfg=cfg_i.get("scan_simulator", {}),
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deflection_cfg=cfg_i["panel_deflection"],
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)
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sample_id = (
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f"r{th_r:+.2f}_z{th_z:+.2f}"
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.replace("+", "p").replace("-", "n").replace(".", "")
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)
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ply_path = out_dir / f"cloud_{sample_id}.ply"
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# synth.transformed == synth.noisy when transform is disabled.
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write_point_cloud(synth.transformed, ply_path)
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manifest.append({
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"sample_id": sample_id,
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"ply": ply_path.name,
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"theta_right_deg": float(th_r),
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"theta_ref_deg": float(th_z),
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"n_points": int(synth.transformed.shape[0]),
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})
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write_json(
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{
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"stp": str(args.stp),
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"profile": args.profile,
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"gt": "gt.json",
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"samples": manifest,
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},
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out_dir / "manifest.json",
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)
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log.info("done: %d clouds + gt.json + manifest.json under %s", len(manifest), out_dir)
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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@@ -0,0 +1,58 @@
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"""Minimal integration example for software developers.
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This script shows the *only* code path a production caller needs:
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load a clean, registered point cloud → call the API → use the result
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Run::
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python examples/integrate_minimal.py path/to/scan.ply
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"""
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from __future__ import annotations
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import logging
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import sys
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from pathlib import Path
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from coupler_panel import (
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CouplerError,
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compute_coupler_measurement,
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load_point_cloud,
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)
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def main(input_path: Path) -> int:
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logging.basicConfig(level=logging.INFO, format="%(levelname)s %(name)s: %(message)s")
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log = logging.getLogger("integrate_minimal")
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points = load_point_cloud(input_path)
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log.info("loaded %d points from %s", points.shape[0], input_path)
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try:
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result = compute_coupler_measurement(
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points,
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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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print(f"theta_right_deg = {result.theta_right_deg:+.4f}")
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print(f"theta_ref_deg = {result.theta_ref_deg:+.4f}")
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print(f"D_y_max_mm = {result.D_y_max_mm:.3f}")
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print(f"D_z_max_mm = {result.D_z_max_mm:.3f}")
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print(f"dx_y_max_mm = {result.dx_y_max_mm:.3f}")
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print(f"dx_z_max_mm = {result.dx_z_max_mm:.3f}")
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print(f"center_C = {tuple(round(c, 3) for c in result.center_C)}")
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print(f"normal = {tuple(round(c, 6) for c in result.normal)}")
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print(f"quality_flags = {result.quality_flags}")
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return 0
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if __name__ == "__main__":
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if len(sys.argv) != 2:
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print(__doc__.strip())
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sys.exit(1)
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sys.exit(main(Path(sys.argv[1])))
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@@ -0,0 +1,8 @@
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{
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"x_min": -12000.0,
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"x_max": 100.0,
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"y_min": -300.0,
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"y_max": 1200.0,
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"z_min": -1000.0,
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"z_max": 800.0
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}
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@@ -0,0 +1,9 @@
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{
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"x_min": 11526.0,
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"x_max": 11733.0,
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"y_min": 588.0,
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"y_max": 1192.0,
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"z_min": -950.0,
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"z_max": 950.0,
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"comment": "Coupler mounting panel ROI on train_2 full-vehicle scan. Dataset frame: x=length, y=height, z=width. These six numbers are the cropping hyper-parameters consumed directly by the algorithm."
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}
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"""Batch evaluator: main measurement program with CAD + cloud + ROI inputs.
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For each PLY listed in the manifest:
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1. Load the cloud (PLY).
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2. Apply the ROI JSON (currently ``mode='all'`` placeholder).
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3. Feed (CAD STP, ROI'd cloud, GT JSON) into the existing measurement
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pipeline — internal stages (denoise / Kabsch / detection / ROI /
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plane fit / metrics) are unchanged.
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4. Compare θ_right / θ_ref against the injected GT recorded in the
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manifest.
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5. Append a row to the Excel report.
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Run::
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python examples/run_batch_eval.py \
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--cad test_data/lu1.stp \
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--data test_data/synth \
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--roi examples/roi_all.json \
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--out runs/batch_eval \
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--profile lu1_af4
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"""
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from __future__ import annotations
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import argparse
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import json
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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.io_utils import load_point_cloud
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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("--cad", type=Path, required=True, help="STEP file (panel CAD).")
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p.add_argument("--data", type=Path, required=True, help="Directory with PLYs + manifest.json.")
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p.add_argument("--roi", type=Path, required=True, help="ROI JSON file.")
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p.add_argument("--out", type=Path, required=True, help="Output directory for runs + xlsx.")
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p.add_argument("--profile", type=str, default="lu1_af4", help="Config profile.")
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p.add_argument("--config", type=Path, default=None, help="Optional YAML override.")
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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_batch_eval")
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args = _build_parser().parse_args(argv)
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args.out.mkdir(parents=True, exist_ok=True)
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manifest_path = args.data / "manifest.json"
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with manifest_path.open("r", encoding="utf-8") as fh:
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manifest = json.load(fh)
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samples = manifest["samples"]
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roi_spec = load_roi_json(args.roi)
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log.info(
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"loaded ROI spec (%s): x∈[%g,%g] y∈[%g,%g] z∈[%g,%g]",
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roi_spec.kind,
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roi_spec.x_min, roi_spec.x_max,
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roi_spec.y_min, roi_spec.y_max,
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roi_spec.z_min, roi_spec.z_max,
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)
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log.info("samples in manifest: %d", len(samples))
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rows = []
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for i, sample in enumerate(samples, start=1):
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sid = sample["sample_id"]
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ply = args.data / sample["ply"]
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log.info("[%d/%d] %s — %s", i, len(samples), sid, ply.name)
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run_dir = args.out / sid
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try:
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# Pre-count points to record n_points_in (before ROI).
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n_in = int(load_point_cloud(ply).shape[0])
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# Main pipeline: CAD STP is parsed for the panel-normal seed
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# only; the cloud is assumed to be in the CAD frame already
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# (scanner extrinsics calibrated upstream). No Kabsch.
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# The wall-clock duration from "inputs enter the algorithm"
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# to "result returned" goes straight into the Excel report.
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t_start = time.perf_counter()
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result = run_coupler_measurement_pipeline(
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input_cloud=ply,
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out_dir=run_dir,
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config_path=args.config,
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profile=args.profile,
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cad_stp_path=args.cad,
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roi_spec=roi_spec,
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)
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pipeline_seconds = time.perf_counter() - t_start
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except CouplerError as exc:
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log.error(" -> FAILED: %s", exc)
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continue
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except Exception as exc:
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log.exception(" -> CRASH: %s", exc)
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continue
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# n_after_roi is recorded in run_dir/roi.json.diagnostics.n_out
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roi_diag_path = run_dir / "roi.json"
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n_after = n_in
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if roi_diag_path.exists():
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with roi_diag_path.open("r", encoding="utf-8") as fh:
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n_after = int(json.load(fh).get("diagnostics", {}).get("n_out", n_in))
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# Kabsch RMSE: pull from the prepared/registration log if present
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# (the persisted pipeline does not currently expose this in the
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# report dict; it's available via report.json side-files but for a
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# minimum-touch wiring we leave it None when not surfaced).
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registration = None
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row = build_row_from_summary(
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sample_id=sid,
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ply_path=str(ply),
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roi_kind=roi_spec.kind,
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measured=result.to_dict(),
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gt_angles=(float(sample["theta_right_deg"]), float(sample["theta_ref_deg"])),
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registration=registration,
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n_points_in=n_in,
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n_points_after_roi=n_after,
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pipeline_seconds=pipeline_seconds,
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)
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rows.append(row)
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log.info(" θ_right pred=%+.4f° GT=%+.2f° err=%+.4f°",
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row.theta_right_pred_deg, row.theta_right_gt_deg, row.theta_right_err_deg)
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log.info(" θ_ref pred=%+.4f° GT=%+.2f° err=%+.4f°",
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row.theta_ref_pred_deg, row.theta_ref_gt_deg, row.theta_ref_err_deg)
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log.info(" runtime: %.3f s (inner stages: %.3f s)",
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row.pipeline_seconds, row.inner_stage_seconds)
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if not rows:
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log.error("no successful runs; nothing to write")
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return 2
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xlsx_path = args.out / "eval_report.xlsx"
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write_excel_report(rows, xlsx_path)
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log.info("wrote %s (%d rows)", xlsx_path, len(rows))
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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@@ -0,0 +1,43 @@
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"""Full research demo: STP → synthetic cloud → measure → diff GT.
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Run::
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python examples/run_full_validation.py path/to/panel.stp runs/demo
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"""
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from __future__ import annotations
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import json
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import logging
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import sys
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from pathlib import Path
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from coupler_panel.pipeline import run_from_cad_pipeline
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def main(stp: Path, out: Path) -> int:
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logging.basicConfig(level=logging.INFO, format="%(levelname)s %(name)s: %(message)s")
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summary = run_from_cad_pipeline(
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stp_path=stp,
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out_dir=out,
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progress=lambda s, f: print(f"[{f*100:5.1f}%] {s}", flush=True),
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)
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print("\n=== diff (measured - GT) ===")
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print(json.dumps(summary["diff"], indent=2))
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# Render diagnostic PNGs.
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try:
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from coupler_panel.viz import render_all
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render_all(out)
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except ImportError:
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print("(matplotlib not installed; skip rendering)")
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return 0
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if __name__ == "__main__":
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if len(sys.argv) != 3:
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print(__doc__.strip())
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sys.exit(1)
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sys.exit(main(Path(sys.argv[1]), Path(sys.argv[2])))
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@@ -0,0 +1,113 @@
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"""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:
|
||||
p = argparse.ArgumentParser(description=__doc__)
|
||||
p.add_argument("--roi", type=Path, required=True, help="ROI JSON (6-key AABB).")
|
||||
p.add_argument("--cloud", type=Path, required=True, help="Full-vehicle point cloud PLY.")
|
||||
p.add_argument("--stp", type=Path, default=None, help="Theoretical CAD STEP (audit).")
|
||||
p.add_argument("--out", type=Path, required=True, help="Output directory.")
|
||||
p.add_argument("--profile", type=str, default="train2_coupler",
|
||||
help="Config profile (default: train2_coupler).")
|
||||
p.add_argument("--config", type=Path, default=None, help="Optional YAML override.")
|
||||
p.add_argument("--gt-theta-right", type=float, default=0.0,
|
||||
help="Known/expected theta_right (deg) for the error column. Default 0.")
|
||||
p.add_argument("--gt-theta-ref", type=float, default=0.0,
|
||||
help="Known/expected theta_ref (deg) for the error column. Default 0.")
|
||||
p.add_argument("--sample-id", type=str, default=None, help="Row label in the report.")
|
||||
return p
|
||||
|
||||
|
||||
def main(argv: list[str] | None = None) -> int:
|
||||
logging.basicConfig(level=logging.INFO, format="%(levelname)s %(name)s: %(message)s")
|
||||
log = logging.getLogger("run_integration")
|
||||
args = _build_parser().parse_args(argv)
|
||||
|
||||
roi_spec = load_roi_json(args.roi)
|
||||
log.info("ROI bbox: x[%g,%g] y[%g,%g] z[%g,%g]",
|
||||
roi_spec.x_min, roi_spec.x_max, roi_spec.y_min,
|
||||
roi_spec.y_max, roi_spec.z_min, roi_spec.z_max)
|
||||
log.info("cloud: %s", args.cloud)
|
||||
log.info("stp (audit): %s", args.stp)
|
||||
|
||||
sample_id = args.sample_id or args.cloud.stem
|
||||
|
||||
t0 = time.perf_counter()
|
||||
try:
|
||||
result = run_coupler_measurement_pipeline(
|
||||
input_cloud=args.cloud,
|
||||
out_dir=args.out,
|
||||
config_path=args.config,
|
||||
profile=args.profile,
|
||||
roi_spec=roi_spec,
|
||||
progress=lambda s, f: log.info("[%5.1f%%] %s", f * 100, s),
|
||||
)
|
||||
except CouplerError as exc:
|
||||
log.error("measurement failed: %s", exc)
|
||||
return 2
|
||||
pipeline_seconds = time.perf_counter() - t0
|
||||
|
||||
# n_points after ROI crop is recorded in <out>/roi.json diagnostics.
|
||||
import json as _json
|
||||
roi_diag = _json.loads((args.out / "roi.json").read_text(encoding="utf-8"))
|
||||
n_roi = int(roi_diag.get("diagnostics", {}).get("n_out", 0))
|
||||
n_in = int(roi_diag.get("diagnostics", {}).get("n_in", n_roi))
|
||||
|
||||
row = build_row_from_summary(
|
||||
sample_id=sample_id,
|
||||
ply_path=str(args.cloud),
|
||||
roi_kind=f"aabb {roi_spec.x_min:.0f}-{roi_spec.x_max:.0f},"
|
||||
f"{roi_spec.y_min:.0f}-{roi_spec.y_max:.0f},"
|
||||
f"{roi_spec.z_min:.0f}-{roi_spec.z_max:.0f}",
|
||||
measured=result.to_dict(),
|
||||
gt_angles=(args.gt_theta_right, args.gt_theta_ref),
|
||||
registration=None,
|
||||
n_points_in=n_in,
|
||||
n_points_after_roi=n_roi,
|
||||
pipeline_seconds=pipeline_seconds,
|
||||
)
|
||||
# Record the STP path in the row's extra metadata (audit trail).
|
||||
row.extra["stp_audit_path"] = str(args.stp) if args.stp else ""
|
||||
|
||||
xlsx = write_excel_report([row], args.out / "eval_report.xlsx")
|
||||
log.info("theta_right=%+.4f theta_ref=%+.4f flags=%s",
|
||||
result.theta_right_deg, result.theta_ref_deg, result.quality_flags)
|
||||
log.info("wrote %s", xlsx)
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
raise SystemExit(main())
|
||||
Reference in New Issue
Block a user