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from transformers import TrOCRProcessor, VisionEncoderDecoderModel | |
from PIL import Image | |
import re | |
# Load model + processor | |
processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-stage1") | |
model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-base-stage1") | |
def extract_weight(image: Image.Image) -> str: | |
image = image.convert("RGB") | |
pixel_values = processor(images=image, return_tensors="pt").pixel_values | |
generated_ids = model.generate(pixel_values) | |
full_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0] | |
# Lowercase text but don't strip spacing before kg detection | |
full_text_lower = full_text.lower() | |
# Detect unit | |
if "kg" in full_text_lower.replace(" ", ""): | |
unit = "kg" | |
elif "g" in full_text_lower.replace(" ", "") or "gram" in full_text_lower: | |
unit = "grams" | |
else: | |
unit = "grams" # default | |
# Extract number using regex | |
match = re.search(r"(\d+(\.\d+)?)", full_text) | |
if match: | |
weight = match.group(1) | |
return f"{weight} {unit}" | |
else: | |
return "No valid weight detected" | |