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""" |
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Download script for structured3d dataset chunks from Hugging Face |
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""" |
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import os |
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import sys |
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from pathlib import Path |
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try: |
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from huggingface_hub import hf_hub_download, list_repo_files |
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except ImportError: |
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print("Error: huggingface_hub not installed") |
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print("Install with: pip install huggingface_hub") |
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sys.exit(1) |
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DATASET_NAME = "structured3d" |
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DEFAULT_REPO_ID = f"your-username/{DATASET_NAME}-dataset" |
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def download_chunks(repo_id, token=None): |
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"""Download structured3d chunks from Hugging Face.""" |
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try: |
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files = list_repo_files(repo_id=repo_id, repo_type="dataset", token=token) |
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chunk_files = [f for f in files if f.startswith(f"{DATASET_NAME}/{DATASET_NAME}_part_")] |
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if not chunk_files: |
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print(f"Error: No chunks found in {repo_id}") |
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print(f"Expected files like {DATASET_NAME}/{DATASET_NAME}_part_000") |
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return False |
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print(f"Found {len(chunk_files)} chunks to download") |
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print(f"Warning: This will download ~307GB of data. Ensure you have enough disk space!") |
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response = input("Continue with download? (y/N): ") |
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if response.lower() != 'y': |
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print("Download cancelled.") |
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return False |
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chunks_dir = Path("chunks") |
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chunks_dir.mkdir(exist_ok=True) |
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for i, file_path in enumerate(sorted(chunk_files)): |
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chunk_name = Path(file_path).name |
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local_path = chunks_dir / chunk_name |
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print(f"Downloading {chunk_name} ({i+1}/{len(chunk_files)})...") |
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try: |
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hf_hub_download( |
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repo_id=repo_id, |
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repo_type="dataset", |
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filename=file_path, |
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local_dir=".", |
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token=token |
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) |
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downloaded_path = Path(file_path) |
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if downloaded_path.exists(): |
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downloaded_path.rename(local_path) |
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except Exception as e: |
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print(f" ✗ Error downloading {chunk_name}: {e}") |
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continue |
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helper_files = [f for f in files if f.startswith(f"{DATASET_NAME}/") and f.endswith(('.sh', '.py'))] |
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for file_path in helper_files: |
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script_name = Path(file_path).name |
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if script_name != "download.py": |
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print(f"Downloading {script_name}...") |
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try: |
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hf_hub_download( |
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repo_id=repo_id, |
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repo_type="dataset", |
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filename=file_path, |
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local_dir=".", |
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token=token |
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) |
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downloaded_path = Path(file_path) |
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if downloaded_path.exists(): |
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downloaded_path.rename(script_name) |
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if script_name.endswith('.sh'): |
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os.chmod(script_name, 0o755) |
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except Exception as e: |
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print(f" ✗ Error downloading {script_name}: {e}") |
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dataset_dir = Path(DATASET_NAME) |
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if dataset_dir.exists() and not any(dataset_dir.iterdir()): |
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dataset_dir.rmdir() |
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print(f"\n✓ Download complete!") |
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print(f"Downloaded {len(chunk_files)} chunks to chunks/ directory") |
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print("\nNext steps:") |
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print("1. Run ./merge.sh to reassemble the original file") |
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print("2. Run ./extract.sh to extract contents") |
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print("\nWarning: Extraction will require additional ~307GB of disk space!") |
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return True |
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except Exception as e: |
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print(f"Error accessing repository {repo_id}: {e}") |
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return False |
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def main(): |
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import argparse |
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parser = argparse.ArgumentParser(description=f"Download {DATASET_NAME} chunks from Hugging Face") |
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parser.add_argument("repo_id", nargs="?", default=DEFAULT_REPO_ID, help="Hugging Face repository ID") |
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parser.add_argument("--token", help="Hugging Face token (or set HF_TOKEN env var)") |
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args = parser.parse_args() |
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token = args.token or os.getenv("HF_TOKEN") |
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print(f"Downloading from: {args.repo_id}") |
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success = download_chunks( |
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repo_id=args.repo_id, |
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token=token |
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) |
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if not success: |
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sys.exit(1) |
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if __name__ == "__main__": |
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main() |