lipan
29f1d45d66
算法更新: delivery v1.2.1、平整度v1.5、测距v2.2、整车配准v1.3 适配器: vehicle-registration 新增、各算法 manifest 和 adapter 更新 后端: taskCadFiles/source 字段迁移、derivedPointClouds 注册、取消任务联动 前端: ElapsedTime 时长显示、两步算法流程、canRun 逻辑修复 文档: 新增5份算法性能分析报告
182 lines
7.0 KiB
Python
182 lines
7.0 KiB
Python
"""vehicle-registration 整车配准适配器 (v1.3)。
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调用 alg/整车配准v1.3 的 translate_align_by_front_tail：
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- 输入：整车点云 PLY + 标准 STEP CAD
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- 原理：车头/车尾各采样少量点算质心差，融合成整体平移矩阵
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- v1.3 新增：ICP 精配准、CAD 采样缓存、配准误差统计（RMSE/p95/p99）
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- 输出：
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aligned_pointcloud_translation_only.ply 配准后的完整点云
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T_translation_only.txt 4x4 平移矩阵
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result.json 额外约定 derivedPointClouds 字段：runner 会把列出的 PLY
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回写为该任务的新点云记录（source='registered'），供后续测量算法选用。
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"""
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from __future__ import annotations
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import os
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import sys
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import traceback
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent))
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from _plugin_io import (
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emit_progress,
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first_pointcloud,
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load_input,
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write_error_result,
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write_result,
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)
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def main() -> int:
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payload = load_input(sys.argv)
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inputs = payload.get("inputs") or {}
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config = inputs.get("config") or {}
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out_dir = Path(payload["outDir"])
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out_dir.mkdir(parents=True, exist_ok=True)
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try:
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emit_progress(0.05, "加载整车配准算法包 v1.3")
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from translate_align_pointcloud_to_cad import translate_align_by_front_tail # type: ignore
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pc_path = first_pointcloud(payload)
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cad_path = inputs.get("cadPath")
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if not cad_path:
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raise RuntimeError("整车配准需要 STEP CAD 文件，请在任务下上传并选中 CAD。")
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axis = str(config.get("axis") or "x")
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crop_ratio = float(config.get("cropRatio") or 0.01)
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mesh_deflection = float(config.get("meshDeflection") or 0.1)
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cad_sample_points = int(config.get("cadSamplePoints") or 30000)
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local_sample_points = int(config.get("localSamplePoints") or 1000)
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scale_pointcloud = float(config.get("scalePointcloud") or 1.0)
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# v1.3 新增参数
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use_icp = bool(config.get("useIcp") if config.get("useIcp") is not None else True)
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icp_sample_points = int(config.get("icpSamplePoints") or 200000)
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compute_error_stats = bool(config.get("computeErrorStats") if config.get("computeErrorStats") is not None else True)
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use_cad_cache = bool(config.get("useCadCache") if config.get("useCadCache") is not None else True)
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emit_progress(
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0.15,
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f"开始配准：{os.path.basename(pc_path)} ← {os.path.basename(str(cad_path))}"
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+ (" + ICP" if use_icp else ""),
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)
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result = translate_align_by_front_tail(
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cad_path=str(cad_path),
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pointcloud_path=pc_path,
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output_dir=str(out_dir),
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axis=axis,
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crop_ratio=crop_ratio,
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mesh_deflection=mesh_deflection,
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cad_sample_points=cad_sample_points,
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local_sample_points=local_sample_points,
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scale_pointcloud=scale_pointcloud,
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visualize=False,
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use_cad_cache=use_cad_cache,
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use_icp=use_icp,
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icp_sample_points=icp_sample_points,
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compute_error_stats=compute_error_stats,
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save_debug_samples=False,
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)
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emit_progress(0.92, "整理结果")
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t_final = [float(v) for v in result["translation"]]
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ft_diff = float(result["front_tail_translation_difference"])
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elapsed = float(result.get("elapsed_seconds") or 0)
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measurements = [
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{"name": "最终平移量 Tx", "value": t_final[0], "unit": "mm", "status": "info"},
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{"name": "最终平移量 Ty", "value": t_final[1], "unit": "mm", "status": "info"},
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{"name": "最终平移量 Tz", "value": t_final[2], "unit": "mm", "status": "info"},
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{
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"name": "前后端平移差",
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"value": ft_diff,
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"unit": "mm",
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"tolerance": 50.0,
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"status": "pass" if ft_diff <= 50.0 else "warning",
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},
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]
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# ICP 结果指标
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icp_stats = result.get("icp_stats")
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if icp_stats:
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measurements.append({
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"name": "ICP fitness",
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"value": float(icp_stats.get("fitness", 0)),
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"unit": "",
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"status": "pass" if float(icp_stats.get("fitness", 0)) >= 0.9 else "warning",
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})
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measurements.append({
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"name": "ICP inlier RMSE",
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"value": float(icp_stats.get("inlier_rmse", 0)),
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"unit": "mm",
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"status": "info",
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})
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# 配准误差统计
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error_stats = result.get("error_stats")
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if error_stats:
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rmse = float(error_stats.get("rmse", 0))
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p95 = float(error_stats.get("p95", 0))
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measurements += [
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{"name": "配准 RMSE", "value": rmse, "unit": "mm",
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"status": "pass" if rmse <= 5.0 else "warning"},
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{"name": "配准误差 p95", "value": p95, "unit": "mm", "status": "info"},
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{"name": "配准误差 p99", "value": float(error_stats.get("p99", 0)), "unit": "mm", "status": "info"},
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]
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aligned_name = Path(result["aligned_path"]).name
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src_stem = Path(pc_path).stem
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# 下载文件：矩阵 + 误差统计（如有）
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files = [Path(result["matrix_path"]).name]
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error_stats_path = result.get("error_stats_path")
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if error_stats_path and Path(error_stats_path).exists():
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files.append(Path(error_stats_path).name)
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payload_out = {
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"schemaVersion": 1,
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"status": "completed",
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"message": (
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f"整车配准完成（{'平移 + ICP' if use_icp else '仅平移'}，耗时 {elapsed:.1f}s）。"
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"配准后的点云已加入任务点云列表，请在后续算法中选用。"
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),
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"measurements": measurements,
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"overlay3d": {"kind": "none"},
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"files": files,
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"derivedPointClouds": [
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{"file": aligned_name, "name": f"{src_stem}_已配准.ply"}
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],
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"extra": {
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"initialTranslation": [float(v) for v in result.get("initial_translation", result["translation"])],
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"finalTranslation": t_final,
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"tFront": [float(v) for v in result["t_front"]],
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"tTail": [float(v) for v in result["t_tail"]],
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"matrix": [[float(v) for v in row] for row in result["T_final"]],
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"icpStats": icp_stats,
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"elapsedSeconds": elapsed,
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"sourcePointCloud": os.path.basename(pc_path),
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"cad": os.path.basename(str(cad_path)),
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},
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}
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write_result(out_dir, payload_out)
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emit_progress(1.0, "完成")
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return 0
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except Exception as exc:
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traceback.print_exc()
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write_error_result(
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out_dir,
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f"整车配准失败：{exc}",
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extra={"traceback": traceback.format_exc()},
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)
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return 1
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if __name__ == "__main__":
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sys.exit(main())
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