| from __future__ import annotations |
|
|
| import hashlib |
| from collections import Counter |
| from pathlib import Path |
|
|
| from PIL import Image |
|
|
| from .io import image_path, metadata_path, read_json, read_jsonl |
|
|
|
|
| REQUIRED_FIELDS = { |
| "id", |
| "file_name", |
| "dimension_id", |
| "dimension_name", |
| "task_group_id", |
| "task_group_name", |
| "task_name", |
| "user_prompt", |
| "last_frame_goal", |
| "progress_goal", |
| "foreground_rule", |
| "background_rule", |
| "implicit_rule", |
| "has_progress_goal", |
| "image_width", |
| "image_height", |
| "image_mode", |
| "image_sha256", |
| } |
|
|
|
|
| def file_sha256(path: Path) -> str: |
| digest = hashlib.sha256() |
| with path.open("rb") as handle: |
| for chunk in iter(lambda: handle.read(1024 * 1024), b""): |
| digest.update(chunk) |
| return digest.hexdigest() |
|
|
|
|
| def validate_dataset(dataset_root: str | Path, verify_hashes: bool = True) -> dict: |
| root = Path(dataset_root) |
| rows = read_jsonl(metadata_path(root)) |
| taxonomy = read_json(root / "taxonomy.json") |
| errors: list[str] = [] |
| warnings: list[str] = [] |
|
|
| if len(rows) != 380: |
| errors.append(f"Expected 380 metadata rows, found {len(rows)}") |
| ids = [row.get("id") for row in rows] |
| if ids != list(range(380)): |
| errors.append("IDs are not the contiguous ordered range 0..379") |
|
|
| groups = Counter() |
| dimensions = Counter() |
| for row in rows: |
| missing = REQUIRED_FIELDS - set(row) |
| if missing: |
| errors.append(f"id={row.get('id')}: missing fields {sorted(missing)}") |
| continue |
| groups[row["task_group_id"]] += 1 |
| dimensions[row["dimension_id"]] += 1 |
| if row["has_progress_goal"] != bool(row["progress_goal"]): |
| errors.append(f"id={row['id']}: progress-goal flag is inconsistent") |
|
|
| path = image_path(root, row) |
| if not path.is_file(): |
| errors.append(f"id={row['id']}: missing image {path}") |
| continue |
| try: |
| with Image.open(path) as image: |
| if image.size != (row["image_width"], row["image_height"]): |
| errors.append(f"id={row['id']}: image dimensions do not match metadata") |
| if image.mode != row["image_mode"]: |
| errors.append(f"id={row['id']}: image mode does not match metadata") |
| image.verify() |
| except Exception as exc: |
| errors.append(f"id={row['id']}: invalid image: {exc}") |
| if verify_hashes and file_sha256(path) != row["image_sha256"]: |
| errors.append(f"id={row['id']}: SHA-256 mismatch") |
|
|
| if len(groups) != 38: |
| errors.append(f"Expected 38 task groups, found {len(groups)}") |
| for group_id, count in sorted(groups.items()): |
| if count != 10: |
| errors.append(f"{group_id}: expected 10 rows, found {count}") |
| if len(dimensions) != 9: |
| errors.append(f"Expected 9 dimensions, found {len(dimensions)}") |
| if taxonomy.get("num_task_groups") != len(groups): |
| errors.append("taxonomy.json task-group count does not match metadata") |
|
|
| return { |
| "ok": not errors, |
| "num_rows": len(rows), |
| "num_task_groups": len(groups), |
| "num_dimensions": len(dimensions), |
| "errors": errors, |
| "warning_summary": {}, |
| "warnings": warnings[:20], |
| } |
|
|
