Update ocr_engine.py

ocr_engine.py

@@ -1,9 +1,8 @@
 from transformers import DonutProcessor, VisionEncoderDecoderModel
 from PIL import Image
 import re
-import torch
 
-# Load processor + model
+# Load OCR processor and model (pretrained on receipts, good for 7-segment)
 processor = DonutProcessor.from_pretrained("naver-clova-ix/donut-base-finetuned-cord-v2")
 model = VisionEncoderDecoderModel.from_pretrained("naver-clova-ix/donut-base-finetuned-cord-v2")
 
@@ -11,16 +10,15 @@ def extract_weight(image: Image.Image) -> str:
     image = image.convert("RGB")
     pixel_values = processor(image, return_tensors="pt").pixel_values
 
-    # Generate text prediction
     outputs = model.generate(pixel_values, max_length=512)
     decoded = processor.batch_decode(outputs, skip_special_tokens=True)[0]
 
-    # Clean & extract weight
+    # Extract weight number
     cleaned = decoded.lower().replace(" ", "")
     match = re.search(r"(\d+(\.\d+)?)", cleaned)
     weight = match.group(1) if match else None
 
-    # Detect unit
+    # Smart unit detection
     if any(u in cleaned for u in ["kg", "kgs", "kilogram", "kilo"]):
         unit = "kg"
     elif any(u in cleaned for u in ["g", "gram", "grams"]):