Datasets:

guluthemonster
/

M3VIR

import webdataset as wds
import os
import json
from pathlib import Path
import glob
import argparse

def extract_webdataset(input_path, output_path):
    """
    Extract all WebDataset tar files back to original directory structure
    
    Args:
        input_path: Path to the directory containing WebDataset tar files
        output_path: Directory where to extract the dataset
    """
    # Create base output directory
    os.makedirs(output_path, exist_ok=True)
    
    # Get all tar files
    tar_files = sorted(glob.glob(os.path.join(input_path, "*.tar")))
    print(f"Found {len(tar_files)} tar files")
    
    sample_count = 0
    for tar_idx, tar_file in enumerate(tar_files):
        print(f"\nProcessing tar file {tar_idx + 1}/{len(tar_files)}: {os.path.basename(tar_file)}")
        
        # Initialize WebDataset reader for current tar file
        dataset = wds.WebDataset(
            tar_file,
            shardshuffle=False,
            empty_check=False
        )
        
        for sample in dataset:
            try:
                # Get path information
                path_info = json.loads(sample['path_info.json'])
                
                # Reconstruct directory structure
                category = path_info['category']
                scene = path_info['scene']
                style = path_info['style']
                resolution = path_info['resolution']
           
                
                # Create directories for each image type
                depth_dir = os.path.join(output_path, category, scene, style, 
                                       resolution, "Depth_images")
                id_dir = os.path.join(output_path, category, scene, style, 
                                    resolution, "ID_images")
                rgb_dir = os.path.join(output_path, category, scene, style, 
                                     resolution, "RGB_images")
                
                # Create directories if they don't exist
                os.makedirs(depth_dir, exist_ok=True)
                os.makedirs(id_dir, exist_ok=True)
                os.makedirs(rgb_dir, exist_ok=True)
                
                # Get base filename from key
                base_name = sample['__key__'].split('/')[-1]
                
                # Save Depth files
                depth_exr_path = os.path.join(depth_dir, f"{base_name}.exr")
                depth_json_path = os.path.join(depth_dir, f"{base_name}.json")
                
                with open(depth_exr_path, 'wb') as f:
                    f.write(sample['depth.exr'])
                with open(depth_json_path, 'w') as f:
                    json.dump(json.loads(sample['depth.json']), f, indent=4)
                
                # Save ID files
                id_png_path = os.path.join(id_dir, f"{base_name}.png")
                id_json_path = os.path.join(id_dir, f"{base_name}.json")
                
                with open(id_png_path, 'wb') as f:
                    f.write(sample['id.png'])
                with open(id_json_path, 'w') as f:
                    json.dump(json.loads(sample['id.json']), f, indent=4)
                
                # Save RGB files
                rgb_png_path = os.path.join(rgb_dir, f"{base_name}.png")
                rgb_json_path = os.path.join(rgb_dir, f"{base_name}.json")
                
                with open(rgb_png_path, 'wb') as f:
                    f.write(sample['rgb.png'])
                with open(rgb_json_path, 'w') as f:
                    json.dump(json.loads(sample['rgb.json']), f, indent=4)
                
                sample_count += 1
                if sample_count % 100 == 0:
                    print(f"Extracted {sample_count} samples...")
                    
            except Exception as e:
                print(f"Error extracting sample {sample['__key__']}: {str(e)}")
                continue
    
    print(f"\nExtraction complete. Total samples extracted: {sample_count}")

def verify_extraction(extracted_dir):
    """
    Verify the extraction by counting files
    """
    print("\nVerifying extraction...")
    
    def count_files(directory):
        exr_count = 0
        png_count = 0
        json_count = 0
        
        for root, _, files in os.walk(directory):
            for file in files:
                if file.endswith('.exr'):
                    exr_count += 1
                elif file.endswith('.png'):
                    png_count += 1
                elif file.endswith('.json'):
                    json_count += 1
        
        return {'exr': exr_count, 'png': png_count, 'json': json_count}
    
    # Count files in extracted directory
    extracted_counts = count_files(extracted_dir)
    
    print("\nExtracted file counts:")
    print(f"  EXR files: {extracted_counts['exr']}")
    print(f"  PNG files: {extracted_counts['png']}")
    print(f"  JSON files: {extracted_counts['json']}")
    
    # Basic sanity check
    if extracted_counts['exr'] == 0 or extracted_counts['png'] == 0 or extracted_counts['json'] == 0:
        print("\nWARNING: Some file types have zero count!")
    else:
        print("\nAll file types present in extraction.")

if __name__ == "__main__":
    # Add argument parser
    parser = argparse.ArgumentParser(description='Extract WebDataset back to original format')
    parser.add_argument('--input_path', type=str, required=True,
                        help='Directory containing WebDataset tar files')
    parser.add_argument('--output_path', type=str, required=True,
                        help='Directory where to extract the dataset')
    parser.add_argument('--verify', action='store_true',
                        help='Verify the extraction after completion')
    
    args = parser.parse_args()
    
    print(f"WebDataset path: {args.input_path}")
    print(f"Output directory: {args.output_path}")
    
    print("\nStarting extraction...")
    extract_webdataset(args.input_path, args.output_path)
    
    if args.verify:
        verify_extraction(args.output_path)

	import webdataset as wds
	import os
	import json
	from pathlib import Path
	import glob
	import argparse

	def extract_webdataset(input_path, output_path):
	"""
	Extract all WebDataset tar files back to original directory structure

	Args:
	input_path: Path to the directory containing WebDataset tar files
	output_path: Directory where to extract the dataset
	"""
	# Create base output directory
	os.makedirs(output_path, exist_ok=True)

	# Get all tar files
	tar_files = sorted(glob.glob(os.path.join(input_path, "*.tar")))
	print(f"Found {len(tar_files)} tar files")

	sample_count = 0
	for tar_idx, tar_file in enumerate(tar_files):
	print(f"\nProcessing tar file {tar_idx + 1}/{len(tar_files)}: {os.path.basename(tar_file)}")

	# Initialize WebDataset reader for current tar file
	dataset = wds.WebDataset(
	tar_file,
	shardshuffle=False,
	empty_check=False
	)

	for sample in dataset:
	try:
	# Get path information
	path_info = json.loads(sample['path_info.json'])

	# Reconstruct directory structure
	category = path_info['category']
	scene = path_info['scene']
	style = path_info['style']
	resolution = path_info['resolution']


	# Create directories for each image type
	depth_dir = os.path.join(output_path, category, scene, style,
	resolution, "Depth_images")
	id_dir = os.path.join(output_path, category, scene, style,
	resolution, "ID_images")
	rgb_dir = os.path.join(output_path, category, scene, style,
	resolution, "RGB_images")

	# Create directories if they don't exist
	os.makedirs(depth_dir, exist_ok=True)
	os.makedirs(id_dir, exist_ok=True)
	os.makedirs(rgb_dir, exist_ok=True)

	# Get base filename from key
	base_name = sample['__key__'].split('/')[-1]

	# Save Depth files
	depth_exr_path = os.path.join(depth_dir, f"{base_name}.exr")
	depth_json_path = os.path.join(depth_dir, f"{base_name}.json")

	with open(depth_exr_path, 'wb') as f:
	f.write(sample['depth.exr'])
	with open(depth_json_path, 'w') as f:
	json.dump(json.loads(sample['depth.json']), f, indent=4)

	# Save ID files
	id_png_path = os.path.join(id_dir, f"{base_name}.png")
	id_json_path = os.path.join(id_dir, f"{base_name}.json")

	with open(id_png_path, 'wb') as f:
	f.write(sample['id.png'])
	with open(id_json_path, 'w') as f:
	json.dump(json.loads(sample['id.json']), f, indent=4)

	# Save RGB files
	rgb_png_path = os.path.join(rgb_dir, f"{base_name}.png")
	rgb_json_path = os.path.join(rgb_dir, f"{base_name}.json")

	with open(rgb_png_path, 'wb') as f:
	f.write(sample['rgb.png'])
	with open(rgb_json_path, 'w') as f:
	json.dump(json.loads(sample['rgb.json']), f, indent=4)

	sample_count += 1
	if sample_count % 100 == 0:
	print(f"Extracted {sample_count} samples...")

	except Exception as e:
	print(f"Error extracting sample {sample['__key__']}: {str(e)}")
	continue

	print(f"\nExtraction complete. Total samples extracted: {sample_count}")

	def verify_extraction(extracted_dir):
	"""
	Verify the extraction by counting files
	"""
	print("\nVerifying extraction...")

	def count_files(directory):
	exr_count = 0
	png_count = 0
	json_count = 0

	for root, _, files in os.walk(directory):
	for file in files:
	if file.endswith('.exr'):
	exr_count += 1
	elif file.endswith('.png'):
	png_count += 1
	elif file.endswith('.json'):
	json_count += 1

	return {'exr': exr_count, 'png': png_count, 'json': json_count}

	# Count files in extracted directory
	extracted_counts = count_files(extracted_dir)

	print("\nExtracted file counts:")
	print(f" EXR files: {extracted_counts['exr']}")
	print(f" PNG files: {extracted_counts['png']}")
	print(f" JSON files: {extracted_counts['json']}")

	# Basic sanity check
	if extracted_counts['exr'] == 0 or extracted_counts['png'] == 0 or extracted_counts['json'] == 0:
	print("\nWARNING: Some file types have zero count!")
	else:
	print("\nAll file types present in extraction.")

	if __name__ == "__main__":
	# Add argument parser
	parser = argparse.ArgumentParser(description='Extract WebDataset back to original format')
	parser.add_argument('--input_path', type=str, required=True,
	help='Directory containing WebDataset tar files')
	parser.add_argument('--output_path', type=str, required=True,
	help='Directory where to extract the dataset')
	parser.add_argument('--verify', action='store_true',
	help='Verify the extraction after completion')

	args = parser.parse_args()

	print(f"WebDataset path: {args.input_path}")
	print(f"Output directory: {args.output_path}")

	print("\nStarting extraction...")
	extract_webdataset(args.input_path, args.output_path)

	if args.verify:
	verify_extraction(args.output_path)