| from __future__ import annotations |
|
|
| import json |
| from pathlib import Path |
|
|
| from datasets import Features, Sequence, Value |
|
|
| ROOT = Path(__file__).parent |
|
|
| FEATURES = Features( |
| { |
| "pair_id": Value("string"), |
| "task_family": Value("string"), |
| "task_id": Value("string"), |
| "option_id": Value("string"), |
| "option_description": Value("string"), |
| "natural_image": Value("string"), |
| "tactile_image": Value("string"), |
| "votes_total": Value("int32"), |
| "positives": Value("int32"), |
| "negatives": Value("int32"), |
| "vote_fraction": Value("float32"), |
| "label": Value("int32"), |
| "source_assignments": Value("int32"), |
| "status_counts": Sequence( |
| Features({ |
| "status": Value("string"), |
| "count": Value("int32"), |
| }) |
| ), |
| "used_consensus": Value("bool"), |
| } |
| ) |
|
|
| CONFIGS = { |
| "full": { |
| "description": "All families and options with the official splits.", |
| "data_files": { |
| "train": "processed/splits/train.jsonl", |
| "validation": "processed/splits/val.jsonl", |
| "test": "processed/splits/test.jsonl", |
| }, |
| }, |
| } |
|
|
| for family in ["F1", "F2", "F3", "F4", "F5", "F6"]: |
| CONFIGS[f"family_{family.lower()}"] = { |
| "description": f"Family {family} only.", |
| "data_files": { |
| "train": f"processed/family_splits/{family}/train.jsonl", |
| "validation": f"processed/family_splits/{family}/val.jsonl", |
| "test": f"processed/family_splits/{family}/test.jsonl", |
| }, |
| } |
|
|
|
|
| def count_examples(path: Path) -> int: |
| with path.open("r", encoding="utf-8") as handle: |
| return sum(1 for _ in handle) |
|
|
|
|
| def build_split_info(rel_path: str) -> tuple[int, int]: |
| path = ROOT / rel_path |
| num_bytes = path.stat().st_size |
| num_examples = count_examples(path) |
| return num_examples, num_bytes |
|
|
|
|
| def build_config_entry(name: str, data_files: dict) -> dict: |
| splits = {} |
| dataset_size = 0 |
| for split_name, rel_path in data_files.items(): |
| num_examples, num_bytes = build_split_info(rel_path) |
| dataset_size += num_bytes |
| splits[split_name] = { |
| "name": split_name, |
| "num_examples": num_examples, |
| "num_bytes": num_bytes, |
| } |
| return { |
| "description": CONFIGS[name]["description"], |
| "citation": """@misc{khan2026tactileevalstepautomatedfinegrained, title={TactileEval: A Step Towards Automated Fine-Grained Evaluation and Editing of Tactile Graphics}, author={Adnan Khan and Abbas Akkasi and Majid Komeili}, year={2026}, eprint={2604.19829}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2604.19829}}""", |
| "homepage": "https://tactileeval.github.io/", |
| "license": "mit", |
| "features": FEATURES.to_dict(), |
| "splits": splits, |
| "download_size": dataset_size, |
| "dataset_size": dataset_size, |
| "config_name": name, |
| "data_files": { |
| split: [{"filename": rel_path}] for split, rel_path in data_files.items() |
| }, |
| "default_validation_split": "validation" if "validation" in data_files else None, |
| } |
|
|
|
|
| def main() -> None: |
| info = { |
| name: build_config_entry(name, cfg["data_files"]) |
| for name, cfg in CONFIGS.items() |
| } |
| output_path = ROOT / "dataset_infos.json" |
| with output_path.open("w", encoding="utf-8") as handle: |
| json.dump(info, handle, indent=2) |
| print(f"Wrote {output_path}") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
