Download src/data_loader.py from superhatk/structural-eval-benchmark: direct link, hf CLI and curl.
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https://huggingface.co/datasets/superhatk/structural-eval-benchmark/resolve/main/src/data_loader.py
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hf download hf://datasets/superhatk/structural-eval-benchmark/src/data_loader.py
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curl -L -o data_loader.py https://huggingface.co/datasets/superhatk/structural-eval-benchmark/resolve/main/src/data_loader.py
2.73 kB
| 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) | |
| # 校验图片是否存在 | |
| 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"] # 里面已经存了算好的正确答案 | |
| }) | |
| except Exception as e: | |
| print(f"Error loading {meta_file}: {e}") | |
| # 按 ID 排序,保证顺序固定 (e.g. beam_001 先于 beam_002) | |
| 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 | |
| """ | |
| # 假设文件名规则是 {task_id}.json | |
| # 如果你的 id 是 "frame_001",文件名也是 "frame_001.json" | |
| json_path = self.raw_dir / f"{task_id}.json" | |
| if not json_path.exists(): | |
| # 尝试做一下兼容,有时候 ID 可能不带后缀 | |
| 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 |