Update ocr_engine.py

ocr_engine.py

@@ -3,39 +3,37 @@ import numpy as np
 import cv2
 import re
 
-# Initialize OCR reader once
 reader = easyocr.Reader(['en'], gpu=False)
 
 def extract_weight_from_image(pil_img):
     try:
         img = np.array(pil_img)
 
-        # Convert to grayscale
+        # Grayscale and resize
         gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
-
-        # Resize for better accuracy
         gray = cv2.resize(gray, None, fx=2, fy=2, interpolation=cv2.INTER_LINEAR)
 
-        # Gaussian blur to reduce noise
+        # Enhance contrast
+        gray = cv2.equalizeHist(gray)
         blurred = cv2.GaussianBlur(gray, (3, 3), 0)
-
-        # Invert colors: useful for LCD display images
         inverted = cv2.bitwise_not(blurred)
 
-        # Normalize brightness
-        norm_img = cv2.normalize(inverted, None, 0, 255, cv2.NORM_MINMAX)
-
-        # Perform OCR
-        result = reader.readtext(norm_img, detail=0)
+        # OCR
+        result = reader.readtext(inverted, detail=0)
         combined_text = " ".join(result)
         print("OCR Text:", combined_text)
 
-        # Regex to detect numbers (e.g. 25, 75.45, 100.00)
-        match = re.search(r"\b\d{1,4}(\.\d{1,2})?\b", 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)
         if match:
-            return match.group(), 95.0
+            return f"{match.group(1)} kg", 95.0
         else:
-            return "No weight detected", 0.0
+            # 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
+
+        return "No weight detected kg", 0.0
 
     except Exception as e:
         return f"Error: {str(e)}", 0.0