141 lines
5.5 KiB
Python
141 lines
5.5 KiB
Python
"""B04 지표면 분석 엔진 오케스트레이터.
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원본 LAS를 구조화하고 지면 필터를 실행한 뒤 지표면 5종 모델을 빌드하는
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동기 계산 파이프라인. 라우터에서 asyncio.to_thread로 호출한다.
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"""
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from collections.abc import Callable
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from pathlib import Path
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from typing import Any
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import numpy as np
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from B04_wf1_Surface.B04_wf1_Surface_Engine_Ground import build_ground_masks, summarize_masks
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from B04_wf1_Surface.B04_wf1_Surface_Engine_Pipeline import build_all_terrain_models
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from B04_wf1_Surface.B04_wf1_Surface_Engine_Structurize import structurize_las
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from config.config_system import build_surface_model_config
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# 진행 콜백 시그니처: (진행률 0~100, 현재 단계 키, 메시지)
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ProgressCallback = Callable[[int, str, str], None]
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def _relative_to_project(project_root: Path, path: Path) -> str:
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"""프로젝트 루트 기준 posix 상대 경로 문자열."""
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return path.relative_to(project_root).as_posix()
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def run_surface_analysis(
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project_root: Path,
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las_path: Path,
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*,
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source_filters: list[str],
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methods: list[str],
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force: bool = False,
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on_progress: ProgressCallback | None = None,
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) -> dict[str, Any]:
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"""구조화→필터→모델 빌드를 수행하고 산출 메타데이터를 반환한다.
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반환 dict:
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- processed: {processed_file_path, converted_file_path, point_count, bounds, statistics}
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- ground_summary: 필터별 지면 포인트 요약
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- manifest: 지표면 모델 파이프라인 manifest
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- models: [{model_type, model_file_path, resolution_m, generation_params, layers}]
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"""
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def _report(percent: int, stage: str, message: str) -> None:
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if on_progress is not None:
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on_progress(percent, stage, message)
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stage_root = project_root / "B04_wf1_Surface"
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processed_dir = stage_root / "processed"
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models_dir = stage_root / "models"
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processed_dir.mkdir(parents=True, exist_ok=True)
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models_dir.mkdir(parents=True, exist_ok=True)
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# 1. LAS 구조화 (structured.npz)
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_report(10, "structurize", "LAS 구조화 중")
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structured_path = structurize_las(las_path, processed_dir)
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with np.load(structured_path) as structured:
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xyz = structured["xyz"]
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bounds = structured["bounds"]
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total_points = int(len(xyz))
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stats = {
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"min_z": float(bounds[2, 0]),
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"max_z": float(bounds[2, 1]),
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"mean_z": float(np.mean(xyz[:, 2])) if total_points else None,
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}
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bounds_dict = {
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"x_min": float(bounds[0, 0]),
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"x_max": float(bounds[0, 1]),
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"y_min": float(bounds[1, 0]),
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"y_max": float(bounds[1, 1]),
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}
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data = {"xyz": xyz, "bounds": bounds}
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# 2. 지면 필터 실행
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_report(40, "ground_filter", "지면 필터 적용 중")
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masks = build_ground_masks(data, source_filters)
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ground_summary = summarize_masks(data, masks)
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# 3. 지표면 5종 모델 빌드
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_report(70, "surface_model", "지표면 모델 생성 중")
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config = build_surface_model_config()
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config["source_filters"] = list(source_filters)
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config["precompute"] = list(methods)
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manifest = build_all_terrain_models(data, masks, models_dir, config, force=force)
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_report(95, "saving", "결과 저장 중")
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processed = {
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"processed_file_path": _relative_to_project(project_root, structured_path),
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"converted_file_path": None,
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"point_count": total_points,
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"bounds": bounds_dict,
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"statistics": stats,
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}
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# manifest에서 저장된 모델별 정보 추출 (필터별 대표 모델)
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models: list[dict[str, Any]] = []
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for filter_key, filter_entry in manifest.get("source_filters", {}).items():
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for method, meta in filter_entry.get("methods", {}).items():
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if meta.get("status") != "completed":
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continue
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model_file = meta.get("model_file")
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model_path = (models_dir / model_file) if model_file else None
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layers: list[dict[str, Any]] = []
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if meta.get("preview_file"):
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layers.append(
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{
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"layer_name": f"{method}_{filter_key}_preview",
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"geometry_type": "MESH" if method != "meshfree" else "POINTCLOUD",
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"file_path": _relative_to_project(
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project_root, models_dir / meta["preview_file"]
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),
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"file_format": "glb" if method != "meshfree" else "ply",
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}
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)
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models.append(
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{
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"model_type": method,
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"source_filter": filter_key,
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"representation": meta.get("representation"),
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"model_file_path": _relative_to_project(project_root, model_path)
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if model_path
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else None,
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"resolution_m": meta.get("grid_resolution_meters"),
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"generation_params": {
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"source_filter": filter_key,
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"representation": meta.get("representation"),
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"footprint_area_m2": meta.get("footprint_area_m2"),
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},
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"layers": layers,
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}
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)
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return {
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"processed": processed,
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"ground_summary": ground_summary,
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"manifest": manifest,
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"models": models,
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}
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