from transformers import TrOCRProcessor, VisionEncoderDecoderModel from PIL import Image import torch # Load processor and model only once processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-handwritten") model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-base-handwritten") def extract_weight(image): try: # Resize or preprocess if needed pixel_values = processor(images=image, return_tensors="pt").pixel_values generated_ids = model.generate(pixel_values) text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0] return text.strip() except Exception as e: return f"Error: {str(e)}"