"""
Batch processing example for the Custom OCR Model.
"""

from transformers import AutoModel
from PIL import Image
import os
from pathlib import Path

def batch_ocr_example(image_directory: str):
    """Process multiple images in batch."""
    
    # Load model
    model = AutoModel.from_pretrained("your-username/your-model-name", trust_remote_code=True)
    
    # Get all image files
    image_dir = Path(image_directory)
    image_files = list(image_dir.glob("*.jpg")) + list(image_dir.glob("*.png"))
    
    print(f"Processing {len(image_files)} images...")
    
    results = []
    for image_file in image_files:
        print(f"Processing: {image_file.name}")
        
        # Load image
        image = Image.open(image_file)
        
        # Extract text
        result = model.generate_ocr_text(image, use_native=True)
        
        results.append({
            "filename": image_file.name,
            "text": result["text"],
            "confidence": result["confidence"]
        })
        
        print(f"  Text: {result['text'][:50]}...")
        print(f"  Confidence: {result['confidence']:.3f}")
    
    return results

if __name__ == "__main__":
    import sys
    if len(sys.argv) > 1:
        results = batch_ocr_example(sys.argv[1])
        print(f"\nProcessed {len(results)} images successfully!")
    else:
        print("Usage: python batch_processing.py <image_directory>")