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)}"