Upload structured3d/download.py with huggingface_hub

structured3d/download.py

@@ -0,0 +1,138 @@
+#!/usr/bin/env python3
+"""
+Download script for structured3d dataset chunks from Hugging Face
+"""
+
+import os
+import sys
+from pathlib import Path
+
+try:
+    from huggingface_hub import hf_hub_download, list_repo_files
+except ImportError:
+    print("Error: huggingface_hub not installed")
+    print("Install with: pip install huggingface_hub")
+    sys.exit(1)
+
+DATASET_NAME = "structured3d"
+DEFAULT_REPO_ID = f"your-username/{DATASET_NAME}-dataset"
+
+def download_chunks(repo_id, token=None):
+    """Download structured3d chunks from Hugging Face."""
+    
+    try:
+        # List files in the repository
+        files = list_repo_files(repo_id=repo_id, repo_type="dataset", token=token)
+        
+        # Filter chunk files
+        chunk_files = [f for f in files if f.startswith(f"{DATASET_NAME}/{DATASET_NAME}_part_")]
+        
+        if not chunk_files:
+            print(f"Error: No chunks found in {repo_id}")
+            print(f"Expected files like {DATASET_NAME}/{DATASET_NAME}_part_000")
+            return False
+        
+        print(f"Found {len(chunk_files)} chunks to download")
+        print(f"Warning: This will download ~307GB of data. Ensure you have enough disk space!")
+        
+        response = input("Continue with download? (y/N): ")
+        if response.lower() != 'y':
+            print("Download cancelled.")
+            return False
+        
+        # Create chunks directory
+        chunks_dir = Path("chunks")
+        chunks_dir.mkdir(exist_ok=True)
+        
+        # Download each chunk
+        for i, file_path in enumerate(sorted(chunk_files)):
+            chunk_name = Path(file_path).name
+            local_path = chunks_dir / chunk_name
+            
+            print(f"Downloading {chunk_name} ({i+1}/{len(chunk_files)})...")
+            
+            try:
+                hf_hub_download(
+                    repo_id=repo_id,
+                    repo_type="dataset",
+                    filename=file_path,
+                    local_dir=".",
+                    token=token
+                )
+                
+                # Move to chunks directory
+                downloaded_path = Path(file_path)
+                if downloaded_path.exists():
+                    downloaded_path.rename(local_path)
+                
+            except Exception as e:
+                print(f"  ✗ Error downloading {chunk_name}: {e}")
+                continue
+        
+        # Download helper scripts
+        helper_files = [f for f in files if f.startswith(f"{DATASET_NAME}/") and f.endswith(('.sh', '.py'))]
+        for file_path in helper_files:
+            script_name = Path(file_path).name
+            if script_name != "download.py":  # Don't overwrite ourselves
+                print(f"Downloading {script_name}...")
+                try:
+                    hf_hub_download(
+                        repo_id=repo_id,
+                        repo_type="dataset", 
+                        filename=file_path,
+                        local_dir=".",
+                        token=token
+                    )
+                    
+                    # Move to current directory and make executable
+                    downloaded_path = Path(file_path)
+                    if downloaded_path.exists():
+                        downloaded_path.rename(script_name)
+                        if script_name.endswith('.sh'):
+                            os.chmod(script_name, 0o755)
+                        
+                except Exception as e:
+                    print(f"  ✗ Error downloading {script_name}: {e}")
+        
+        # Clean up empty directories
+        dataset_dir = Path(DATASET_NAME)
+        if dataset_dir.exists() and not any(dataset_dir.iterdir()):
+            dataset_dir.rmdir()
+        
+        print(f"\n✓ Download complete!")
+        print(f"Downloaded {len(chunk_files)} chunks to chunks/ directory")
+        print("\nNext steps:")
+        print("1. Run ./merge.sh to reassemble the original file")
+        print("2. Run ./extract.sh to extract contents")
+        print("\nWarning: Extraction will require additional ~307GB of disk space!")
+        
+        return True
+        
+    except Exception as e:
+        print(f"Error accessing repository {repo_id}: {e}")
+        return False
+
+def main():
+    import argparse
+    
+    parser = argparse.ArgumentParser(description=f"Download {DATASET_NAME} chunks from Hugging Face")
+    parser.add_argument("repo_id", nargs="?", default=DEFAULT_REPO_ID, help="Hugging Face repository ID")
+    parser.add_argument("--token", help="Hugging Face token (or set HF_TOKEN env var)")
+    
+    args = parser.parse_args()
+    
+    # Get token (optional for public repos)
+    token = args.token or os.getenv("HF_TOKEN")
+    
+    print(f"Downloading from: {args.repo_id}")
+    
+    success = download_chunks(
+        repo_id=args.repo_id,
+        token=token
+    )
+    
+    if not success:
+        sys.exit(1)
+
+if __name__ == "__main__":
+    main()