Update ocr_engine.py

ocr_engine.py

@@ -1,32 +1,28 @@
+import pytesseract
 import numpy as np
-import re
 import cv2
-import pytesseract
+import re
 
 def extract_weight_from_image(pil_img):
     try:
         img = np.array(pil_img)
 
-        # Convert to grayscale
+        # Preprocessing
         gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
+        resized = cv2.resize(gray, None, fx=2, fy=2, interpolation=cv2.INTER_CUBIC)
+        blur = cv2.GaussianBlur(resized, (5, 5), 0)
+        _, thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
 
-        # Resize (sharpens small digits)
-        gray = cv2.resize(gray, None, fx=2.5, fy=2.5, interpolation=cv2.INTER_CUBIC)
+        # OCR using pytesseract
+        config = "--psm 6"  # Assume a single uniform block of text
+        text = pytesseract.image_to_string(thresh, config=config)
+        print("OCR Output:", text)
 
-        # Thresholding to clean up image
-        _, thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
-
-        # Run Tesseract OCR
-        custom_config = r'--oem 3 --psm 6'
-        text = pytesseract.image_to_string(thresh, config=custom_config)
-        print("OCR Text:", text)
-
-        # Extract weight pattern like 25.50 or 150
+        # Regex to find weight-like numbers
         match = re.search(r"\b\d{1,4}\.?\d{0,2}\b", text)
         if match:
             return match.group(), 95.0
         else:
             return "No weight detected", 0.0
-
     except Exception as e:
         return f"Error: {str(e)}", 0.0