#!/usr/bin/env python3
"""
Verify xView2 dataset integrity
Checks that all files referenced in JSON metadata exist
"""

import json
from pathlib import Path
from tqdm import tqdm
from collections import defaultdict
from typing import Dict, List, Tuple


def verify_dataset_split(
    json_file: Path,
    base_dir: Path,
    split_name: str,
    verbose: bool = False
) -> Tuple[bool, Dict]:
    """
    Verify a single dataset split
    
    Args:
        json_file: Path to JSON metadata file
        base_dir: Base directory containing the dataset
        split_name: Name of the split (train/test)
        verbose: Print detailed statistics
    
    Returns:
        Tuple of (all_valid, statistics)
    """
    if not json_file.exists():
        if verbose:
            print(f"❌ JSON file not found: {json_file}")
        return False, {}
    
    # Load JSON
    with open(json_file, 'r', encoding='utf-8') as f:
        data = json.load(f)
    
    # Statistics
    stats = {
        'total_entries': len(data),
        'missing_files': [],
        'disaster_types': defaultdict(int),
        'valid_entries': 0,
        'invalid_entries': 0
    }
    
    # Check each entry
    all_valid = True
    
    # Use tqdm only if verbose
    iterator = tqdm(data, desc=f"Checking {split_name}", unit="entry", disable=not verbose) if verbose else data
    
    for idx, entry in enumerate(iterator):
        entry_valid = True
        
        # Count disaster types
        disaster_type = entry.get('disaster_type', 'unknown')
        stats['disaster_types'][disaster_type] += 1
        
        # Check all required fields
        required_fields = [
            'pre_disaster_image',
            'post_disaster_image',
            'pre_disaster_mask',
            'post_disaster_mask',
            'disaster',
            'disaster_type'
        ]
        
        for field in required_fields:
            if field not in entry:
                stats['missing_files'].append({
                    'entry_idx': idx,
                    'field': field,
                    'reason': 'Field missing from JSON'
                })
                entry_valid = False
                continue
            
            # Check if file exists (for image/mask paths)
            if field.endswith('_image') or field.endswith('_mask') or field.endswith('_colormask'):
                file_path = base_dir / entry[field]
                if not file_path.exists():
                    stats['missing_files'].append({
                        'entry_idx': idx,
                        'field': field,
                        'path': str(file_path),
                        'reason': 'File not found'
                    })
                    entry_valid = False
        
        if entry_valid:
            stats['valid_entries'] += 1
        else:
            stats['invalid_entries'] += 1
            all_valid = False
    
    # Print errors if any
    if not all_valid and verbose:
        print(f"\n✗ Invalid entries: {stats['invalid_entries']}")
        print(f"✗ Missing files: {len(stats['missing_files'])}")
        if stats['missing_files']:
            print(f"\nFirst 5 missing files:")
            for missing in stats['missing_files'][:5]:
                print(f"  - Entry {missing['entry_idx']}: {missing['field']} - {missing['reason']}")
                if 'path' in missing:
                    print(f"    Path: {missing['path']}")
    
    return all_valid, stats


def verify_sharegpt_format(
    sharegpt_file: Path,
    split_name: str,
    verbose: bool = False
) -> Tuple[bool, Dict]:
    """
    Verify ShareGPT format file
    
    Args:
        sharegpt_file: Path to ShareGPT JSON file
        split_name: Name of the split
        verbose: Print detailed statistics
    
    Returns:
        Tuple of (all_valid, statistics)
    """
    if not sharegpt_file.exists():
        if verbose:
            print(f"❌ ShareGPT file not found: {sharegpt_file}")
        return False, {}
    
    # Load JSON
    with open(sharegpt_file, 'r', encoding='utf-8') as f:
        conversations = json.load(f)
    
    stats = {
        'total_conversations': len(conversations),
        'valid_conversations': 0,
        'invalid_conversations': 0,
        'languages': defaultdict(int),
        'image_types': defaultdict(int),
        'issues': []
    }
    
    all_valid = True
    
    # Use tqdm only if verbose
    iterator = tqdm(conversations, desc=f"Checking ShareGPT {split_name}", unit="conv", disable=not verbose) if verbose else conversations
    
    for idx, conv in enumerate(iterator):
        conv_valid = True
        
        # Check required fields
        if 'id' not in conv:
            stats['issues'].append(f"Entry {idx}: Missing 'id' field")
            conv_valid = False
        else:
            # Extract language and type from ID
            parts = conv['id'].split('_')
            if len(parts) >= 4:
                img_type = parts[-2]  # pre or post
                lang = parts[-1]      # en, zh, ja
                stats['languages'][lang] += 1
                stats['image_types'][img_type] += 1
        
        if 'images' not in conv or not conv['images']:
            stats['issues'].append(f"Entry {idx}: Missing or empty 'images' field")
            conv_valid = False
        
        if 'messages' not in conv or len(conv['messages']) != 4:
            stats['issues'].append(f"Entry {idx}: Expected 4 messages, got {len(conv.get('messages', []))}")
            conv_valid = False
        else:
            # Check message structure
            messages = conv['messages']
            expected_pattern = ['human', 'gpt', 'human', 'gpt']
            actual_pattern = [m.get('from', '') for m in messages]
            
            if actual_pattern != expected_pattern:
                stats['issues'].append(f"Entry {idx}: Unexpected message pattern {actual_pattern}")
                conv_valid = False
            
            # Check first message has <image> tag
            if messages[0].get('value', '').find('<image>') == -1:
                stats['issues'].append(f"Entry {idx}: First message missing <image> tag")
                conv_valid = False
        
        if conv_valid:
            stats['valid_conversations'] += 1
        else:
            stats['invalid_conversations'] += 1
            all_valid = False
    
    # Print errors if any
    if not all_valid and verbose:
        print(f"\n✗ Invalid conversations: {stats['invalid_conversations']}")
        print(f"\nFirst 5 issues:")
        for issue in stats['issues'][:5]:
            print(f"  - {issue}")
    
    return all_valid, stats


def main():
    """Main verification function"""
    
    import sys
    import argparse
    
    parser = argparse.ArgumentParser(
        description='Verify xView2 dataset integrity',
        formatter_class=argparse.RawDescriptionHelpFormatter,
        epilog='''
Examples:
  # Verify from current directory with default file patterns
  %(prog)s
  
  # Verify specific files
  %(prog)s --train-json xview2_train.json --test-json xview2_test.json
  
  # Verify with verbose output
  %(prog)s --verbose
  
  # Specify custom base directory
  %(prog)s --base-dir /path/to/xview2
        '''
    )
    
    parser.add_argument(
        '--base-dir',
        type=Path,
        default=None,
        help='Base directory containing the dataset (default: current working directory)'
    )
    
    parser.add_argument(
        '--train-json',
        type=str,
        default=None,
        help='Training metadata JSON file name (default: auto-detect xview2_train*.json)'
    )
    
    parser.add_argument(
        '--test-json',
        type=str,
        default=None,
        help='Test metadata JSON file name (default: auto-detect xview2_test*.json)'
    )
    
    parser.add_argument(
        '--train-sharegpt',
        type=str,
        default=None,
        help='Training ShareGPT JSON file name (default: auto-detect xview2_train*_sharegpt.json)'
    )
    
    parser.add_argument(
        '--test-sharegpt',
        type=str,
        default=None,
        help='Test ShareGPT JSON file name (default: auto-detect xview2_test*_sharegpt.json)'
    )
    
    parser.add_argument(
        '-v', '--verbose',
        action='store_true',
        help='Print detailed verification statistics'
    )
    
    parser.add_argument(
        '--skip-original',
        action='store_true',
        help='Skip verification of original metadata files'
    )
    
    parser.add_argument(
        '--skip-sharegpt',
        action='store_true',
        help='Skip verification of ShareGPT format files'
    )
    
    args = parser.parse_args()
    
    # Determine base directory
    base_dir = args.base_dir if args.base_dir else Path.cwd()
    base_dir = base_dir.resolve()
    
    if not base_dir.exists():
        print(f"❌ Base directory does not exist: {base_dir}")
        sys.exit(1)
    
    if not args.verbose:
        print("Verifying dataset integrity...", end=" ", flush=True)
    
    # Auto-detect files if not specified
    def find_file(pattern: str, description: str) -> Path | None:
        """Find a file matching the pattern in base_dir"""
        matches = list(base_dir.glob(pattern))
        if not matches:
            if args.verbose:
                print(f"⚠️  No {description} found matching pattern: {pattern}")
            return None
        if len(matches) > 1:
            if args.verbose:
                print(f"⚠️  Multiple {description} found, using: {matches[0].name}")
        return matches[0]
    
    # Find or use specified files
    train_json = None
    test_json = None
    train_sharegpt = None
    test_sharegpt = None
    
    if not args.skip_original:
        if args.train_json:
            train_json = base_dir / args.train_json
        else:
            # Try to find train JSON (exclude sharegpt files)
            candidates = [f for f in base_dir.glob("*train*.json") if 'sharegpt' not in f.name.lower()]
            train_json = candidates[0] if candidates else None
        
        if args.test_json:
            test_json = base_dir / args.test_json
        else:
            # Try to find test JSON (exclude sharegpt files)
            candidates = [f for f in base_dir.glob("*test*.json") if 'sharegpt' not in f.name.lower()]
            test_json = candidates[0] if candidates else None
    
    if not args.skip_sharegpt:
        if args.train_sharegpt:
            train_sharegpt = base_dir / args.train_sharegpt
        else:
            train_sharegpt = find_file("*train*sharegpt.json", "training ShareGPT file")
        
        if args.test_sharegpt:
            test_sharegpt = base_dir / args.test_sharegpt
        else:
            test_sharegpt = find_file("*test*sharegpt.json", "test ShareGPT file")
    
    # Verify original metadata files
    train_valid = True
    test_valid = True
    train_stats = {}
    test_stats = {}
    
    if not args.skip_original:
        if train_json and train_json.exists():
            train_valid, train_stats = verify_dataset_split(train_json, base_dir, "train", verbose=args.verbose)
        elif args.verbose:
            print(f"⚠️  Skipping train verification: file not found")
            
        if test_json and test_json.exists():
            test_valid, test_stats = verify_dataset_split(test_json, base_dir, "test", verbose=args.verbose)
        elif args.verbose:
            print(f"⚠️  Skipping test verification: file not found")
    
    # Verify ShareGPT format files
    train_sharegpt_valid = True
    test_sharegpt_valid = True
    train_sharegpt_stats = {}
    test_sharegpt_stats = {}
    
    if not args.skip_sharegpt:
        if train_sharegpt and train_sharegpt.exists():
            train_sharegpt_valid, train_sharegpt_stats = verify_sharegpt_format(train_sharegpt, "train", verbose=args.verbose)
        elif args.verbose:
            print(f"⚠️  Skipping train ShareGPT verification: file not found")
            
        if test_sharegpt and test_sharegpt.exists():
            test_sharegpt_valid, test_sharegpt_stats = verify_sharegpt_format(test_sharegpt, "test", verbose=args.verbose)
        elif args.verbose:
            print(f"⚠️  Skipping test ShareGPT verification: file not found")
    
    # Overall summary
    all_checks_passed = train_valid and test_valid and train_sharegpt_valid and test_sharegpt_valid
    
    if not args.verbose:
        print("")  # New line after "Verifying..."
    
    if all_checks_passed:
        print("✅ Dataset is ready")
        if args.verbose:
            print(f"\nVerified in directory: {base_dir}")
            if train_json:
                print(f"  Train JSON: {train_json.name}")
            if test_json:
                print(f"  Test JSON: {test_json.name}")
            if train_sharegpt:
                print(f"  Train ShareGPT: {train_sharegpt.name}")
            if test_sharegpt:
                print(f"  Test ShareGPT: {test_sharegpt.name}")
    else:
        print("❌ Dataset verification failed")
        print("\nIssues found:")
        if not train_valid:
            print(f"  - Training metadata has issues")
        if not test_valid:
            print(f"  - Test metadata has issues")
        if not train_sharegpt_valid:
            print(f"  - Training ShareGPT format has issues")
        if not test_sharegpt_valid:
            print(f"  - Test ShareGPT format has issues")
        print("\nRun with --verbose flag for detailed information")
        sys.exit(1)


if __name__ == "__main__":
    main()