Update ocr_engine.py

ocr_engine.py

@@ -9,29 +9,35 @@ def extract_weight_from_image(pil_img):
     try:
         img = np.array(pil_img)
 
-        # Grayscale and resize
+        # Convert to grayscale
         gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
-        gray = cv2.resize(gray, None, fx=2, fy=2, interpolation=cv2.INTER_LINEAR)
 
         # Enhance contrast
         gray = cv2.equalizeHist(gray)
-        blurred = cv2.GaussianBlur(gray, (3, 3), 0)
-        inverted = cv2.bitwise_not(blurred)
+
+        # Resize to enhance small text
+        gray = cv2.resize(gray, None, fx=2, fy=2, interpolation=cv2.INTER_LINEAR)
+
+        # Add light blur to reduce noise
+        gray = cv2.GaussianBlur(gray, (3, 3), 0)
+
+        # Invert for LCD screens with dark backgrounds
+        inverted = cv2.bitwise_not(gray)
 
         # OCR
         result = reader.readtext(inverted, detail=0)
         combined_text = " ".join(result)
-        print("OCR Text:", combined_text)
+        print("OCR Result:", combined_text)
 
-        # Match weight in KG (like 25kg or 25.00 kg)
-        match = re.search(r'(\d{1,4}(?:\.\d{1,2})?)\s?(kg)', combined_text, re.IGNORECASE)
+        # Try to detect weight pattern like "25kg" or "25.3kg"
+        match = re.search(r"(\d{1,4}(?:\.\d{1,2})?)\s?(kg)", combined_text, re.IGNORECASE)
         if match:
             return f"{match.group(1)} kg", 95.0
-        else:
-            # Fallback to just number
-            fallback = re.search(r'\d{1,4}(?:\.\d{1,2})?', combined_text)
-            if fallback:
-                return f"{fallback.group(0)} kg", 90.0
+
+        # Fallback: detect numbers only
+        fallback = re.search(r"\d{1,4}(?:\.\d{1,2})?", combined_text)
+        if fallback:
+            return f"{fallback.group(0)} kg", 75.0
 
         return "No weight detected kg", 0.0