| |
| """ |
| Download and unpack the objaverse_vida dataset from HuggingFace. |
| |
| This script downloads the dataset and extracts all tar archives to restore |
| the original directory structure expected by downstream consumers. |
| |
| Usage: |
| python unpack.py [target_directory] |
| |
| Example: |
| python unpack.py ./objaverse_vida |
| python unpack.py /data/datasets/objaverse_vida |
| """ |
|
|
| import os |
| import sys |
| import tarfile |
| from pathlib import Path |
|
|
|
|
| def unpack_dataset(target_dir: str = "./objaverse_vida"): |
| """Download and unpack the dataset to the target directory.""" |
| |
| |
| try: |
| from huggingface_hub import snapshot_download |
| except ImportError: |
| print("Error: huggingface_hub not installed.") |
| print("Install with: pip install huggingface_hub[hf_transfer]") |
| sys.exit(1) |
| |
| target = Path(target_dir).resolve() |
| print(f"Target directory: {target}") |
| |
| |
| os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "1" |
| |
| |
| print("\n[1/3] Downloading dataset from HuggingFace...") |
| print(" (This may take a while for ~30GB)") |
| snapshot_download( |
| repo_id="spatial-training/objaverse_vida", |
| repo_type="dataset", |
| local_dir=str(target), |
| local_dir_use_symlinks=False |
| ) |
| print(" Done!") |
| |
| |
| processed_dir = target / "processed_2023_07_28" |
| if processed_dir.exists(): |
| print("\n[2/3] Unpacking processed objects...") |
| shards = sorted(processed_dir.glob("shard_*.tar")) |
| total_shards = len(shards) |
| for i, shard in enumerate(shards, 1): |
| print(f" [{i}/{total_shards}] Extracting {shard.name}...") |
| with tarfile.open(shard) as tar: |
| tar.extractall(processed_dir) |
| shard.unlink() |
| |
| |
| manifest = processed_dir / "manifest.json" |
| if manifest.exists(): |
| manifest.unlink() |
| print(" Done!") |
| else: |
| print("\n[2/3] Skipping processed objects (directory not found)") |
| |
| |
| houses_dir = target / "houses_2023_07_28" |
| if houses_dir.exists(): |
| print("\n[3/3] Unpacking house files...") |
| for split in ["train", "test", "val"]: |
| tar_file = houses_dir / f"{split}_individual.tar" |
| if tar_file.exists(): |
| print(f" Extracting {tar_file.name}...") |
| split_dir = houses_dir / split |
| split_dir.mkdir(exist_ok=True) |
| with tarfile.open(tar_file) as tar: |
| tar.extractall(split_dir) |
| tar_file.unlink() |
| print(" Done!") |
| else: |
| print("\n[3/3] Skipping house files (directory not found)") |
| |
| |
| print("\n" + "=" * 60) |
| print("Dataset unpacked successfully!") |
| print("=" * 60) |
| print(f"\nLocation: {target}") |
| print("\nStructure:") |
| print(" processed_2023_07_28/ - ~40K 3D object directories") |
| print(" houses_2023_07_28/ - train/test/val house layouts") |
| print(" procthor_databases_2023_07_28/ - asset databases") |
| print(" 0.json - sample house") |
|
|
|
|
| def main(): |
| if len(sys.argv) > 1: |
| if sys.argv[1] in ["-h", "--help"]: |
| print(__doc__) |
| sys.exit(0) |
| target = sys.argv[1] |
| else: |
| target = "./objaverse_vida" |
| |
| unpack_dataset(target) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|