Update ocr_engine.py

ocr_engine.py

@@ -3,21 +3,18 @@ import numpy as np
 import cv2
 import re
 
-# Load EasyOCR reader
 reader = easyocr.Reader(['en'], gpu=False)
 
 def extract_weight_from_image(pil_img):
     try:
         img = np.array(pil_img)
 
-        # Resize if large
         max_dim = 1000
         height, width = img.shape[:2]
         if max(height, width) > max_dim:
             scale = max_dim / max(height, width)
             img = cv2.resize(img, None, fx=scale, fy=scale, interpolation=cv2.INTER_AREA)
 
-        # OCR
         results = reader.readtext(img)
         print("DEBUG OCR RESULTS:", results)
 
@@ -26,7 +23,10 @@ def extract_weight_from_image(pil_img):
         fallback_weight = None
         fallback_conf = 0.0
 
-        for _, (text, conf) in results:  # ✅ Correct unpacking
+        for item in results:
+            box, content = item         # ✅ This fixes the unpacking error
+            text, conf = content
+
             original = text
             cleaned = text.lower().strip()
 
@@ -46,7 +46,6 @@ def extract_weight_from_image(pil_img):
             if cleaned.count(".") <= 1 and re.fullmatch(r"\d{2,4}(\.\d{1,3})?", cleaned):
                 weight_candidates.append((cleaned, conf))
 
-        # Choose result
         if weight_candidates:
             best_weight, best_conf = sorted(weight_candidates, key=lambda x: -x[1])[0]
         elif fallback_weight:
@@ -54,7 +53,7 @@ def extract_weight_from_image(pil_img):
         else:
             return "Not detected", 0.0, "OCR returned nothing useful"
 
-        # Clean leading zeros
+        # Remove leading zeros
         if "." in best_weight:
             int_part, dec_part = best_weight.split(".")
             int_part = int_part.lstrip("0") or "0"