feat: initial commit - massive-cloud point cloud processing system

alg/point_porj/config_loader.py

@@ -0,0 +1,104 @@
+from __future__ import annotations
+
+from copy import deepcopy
+from pathlib import Path
+from typing import Any
+
+import yaml
+
+
+DEFAULT_CONFIG: dict[str, Any] = {
+    "paths": {
+        "cad": "CAD/11.step",
+        "mesh": "Mesh/11.stl",
+        "pointcloud": "PointCloud/11.ply",
+        "noisy_pointcloud": "Noise_PointCloud/11_noisy.ply",
+        "output_mesh": "Mesh/11.stl",
+        "curvature_output": None,
+    },
+    "cad": {
+        "precision": 1.0,
+        "enabled": False,
+    },
+    "noise": {
+        "enabled": True,
+        "std": 4.0,
+        "seed": None,
+    },
+    "filters": {
+        "enabled": True,
+        "methods": ["SOR"],
+        "sor_neighbors": 20,
+        "sor_std_ratio": 2.0,
+        "ror_points": 5,
+        "ror_radius": 20.0,
+        "voxel_size": 0.05,
+        "pass_axis": "z",
+        "pass_min": None,
+        "pass_max": None,
+        "bf_sigma_s": 0.01,
+        "bf_sigma_r": 0.1,
+    },
+    "registration": {
+        "voxel_size": 10.0,
+        "roll": 10.0,
+        "pitch": 10.0,
+        "yaw": 10.0,
+        "trans_range": 0.0,
+        "random_seed": None,
+    },
+    "evaluation": {
+        "chunk_size": 2048,
+        "triangle_chunk_size": 4096,
+        "cad_mesh_deflection": 0.1,
+    },
+    "curvature": {
+        "radius": 2.0,
+        "max_nn": 30,
+        "color_scale": 3.0,
+    },
+    "plane": {
+        "size_mm": 1000.0,
+        "noise_std_mm": 0.5,
+        "num_points": 10000,
+        "threshold_mm": 0.5,
+        "max_iterations": 2000,
+    },
+    "visualization": {
+        "enabled": True,
+    },
+}
+
+
+def deep_update(base: dict[str, Any], updates: dict[str, Any]) -> dict[str, Any]:
+    result = deepcopy(base)
+    for key, value in updates.items():
+        if isinstance(value, dict) and isinstance(result.get(key), dict):
+            result[key] = deep_update(result[key], value)
+        else:
+            result[key] = value
+    return result
+
+
+class ConfigLoader:
+    """Load YAML config and merge it with project defaults."""
+
+    def __init__(self, default_config: dict[str, Any] | None = None) -> None:
+        self.default_config = default_config or DEFAULT_CONFIG
+
+    def load(self, config_path: str | None = None) -> dict[str, Any]:
+        config = deepcopy(self.default_config)
+        if not config_path:
+            return config
+
+        path = Path(config_path)
+        if not path.exists():
+            raise FileNotFoundError(f"Config file not found: {path}")
+
+        with path.open("r", encoding="utf-8") as f:
+            user_config = yaml.safe_load(f) or {}
+
+        if not isinstance(user_config, dict):
+            raise ValueError("Config file must contain a YAML mapping at the top level.")
+
+        return deep_update(config, user_config)