@@ -0,0 +1,17 @@
  + from __future__ import annotations
  + from collections import defaultdict
  + 
  + def execute(payload: dict) -> dict:
  +     cell = float(payload.get("cell_size_m", 1))
  +     minimum = int(payload.get("min_points", 2))
  +     if cell <= 0:
  +         raise ValueError("cell_size_m must be positive")
  +     buckets = defaultdict(list)
  +     for point in payload.get("points", []):
  +         buckets[(int(point[0] // cell), int(point[1] // cell))].append(point)
  +     obstacles = []
  +     for key, points in buckets.items():
  +         if len(points) < minimum:
  +             continue
  +         obstacles.append({"cell": list(key), "centroid": [round(sum(p[i] for p in points)/len(points), 3) for i in range(3)], "point_count": len(points), "class": "unknown_obstacle"})
  +     return {"frame": "lidar", "obstacles": obstacles, "obstacle_count": len(obstacles)}

added examples/input.json +21−0 View file

@@ -0,0 +1,21 @@
  + {
  +   "cell_size_m": 1,
  +   "min_points": 2,
  +   "points": [
  +     [
  +       1.1,
  +       2.1,
  +       0.3
  +     ],
  +     [
  +       1.2,
  +       2.2,
  +       0.5
  +     ],
  +     [
  +       8,
  +       9,
  +       0.2
  +     ]
  +   ]
  + }

added pyproject.toml +8−0 View file

@@ -0,0 +1,8 @@
  + [project]
  + name = "3d_environment_perception"
  + version = "0.1.0"
  + description = "3차원 점군을 격자 군집화해 장애물 위치와 경계 상자를 생성합니다."
  + requires-python = ">=3.11"
  + 
  + [tool.unittest]
  + test-path = "tests"

added run.py +10−0 View file

@@ -0,0 +1,10 @@
  + from __future__ import annotations
  + import json
  + import sys
  + from asw_component import execute
  + 
  + if __name__ == "__main__":
  +     path = sys.argv[1] if len(sys.argv) > 1 else None
  +     with open(path, encoding="utf-8") if path else sys.stdin as source:
  +         payload = json.load(source)
  +     print(json.dumps(execute(payload), ensure_ascii=False, indent=2))