| import json |
| import os |
| from pathlib import Path |
|
|
| class BenchmarkDataLoader: |
| def __init__(self, data_root="data"): |
| self.root = Path(data_root) |
| self.img_dir = self.root / "images" |
| self.meta_dir = self.root / "ground_truth_meta" |
| self.raw_dir = self.root / "raw_models" |
|
|
| def load_tasks_for_eval(self): |
| """ |
| 加载用于评测的任务列表 (只读 meta 和图片) |
| """ |
| tasks = [] |
| if not self.meta_dir.exists(): |
| print(f"Warning: {self.meta_dir} does not exist. Please run tools/generate_gt.py first.") |
| return [] |
|
|
| for meta_file in self.meta_dir.glob("*.json"): |
| try: |
| with open(meta_file, 'r', encoding='utf-8') as f: |
| meta = json.load(f) |
| |
| |
| img_name = meta.get("image_filename") |
| img_path = self.img_dir / img_name |
| if not img_path.exists(): |
| print(f"Skipping {meta_file.name}: Image not found at {img_path}") |
| continue |
|
|
| tasks.append({ |
| "id": meta["id"], |
| "difficulty": meta.get("difficulty", 1), |
| "image_path": str(img_path), |
| "gt_solution": meta["solution"] |
| }) |
| except Exception as e: |
| print(f"Error loading {meta_file}: {e}") |
| |
| |
| tasks.sort(key=lambda x: x['id']) |
| |
| return tasks |
|
|
| def load_raw_models(self): |
| """ |
| 加载原始 JSON 模型 (用于 tools/generate_gt.py 生成真值) |
| """ |
| models = [] |
| for json_file in self.raw_dir.glob("*.json"): |
| models.append({ |
| "id": json_file.stem, |
| "path": str(json_file), |
| "filename": json_file.name |
| }) |
| return models |
|
|
| def load_raw_model_by_id(self, task_id): |
| """ |
| [Debug模式专用] 根据 Task ID 读取原始的正确 JSON 文件 |
| """ |
| |
| |
| json_path = self.raw_dir / f"{task_id}.json" |
|
|
| if not json_path.exists(): |
| |
| return None |
|
|
| try: |
| with open(json_path, 'r', encoding='utf-8') as f: |
| return json.load(f) |
| except Exception as e: |
| print(f"Error reading raw model {json_path}: {e}") |
| return None |