Update ocr_engine.py

ocr_engine.py

@@ -1,44 +1,40 @@
-import easyocr
+import pytesseract
 import numpy as np
 import cv2
 import re
-
-reader = easyocr.Reader(['en'], gpu=False)
+from PIL import Image
 
 def extract_weight_from_image(pil_img):
     try:
         img = np.array(pil_img)
 
-        # Resize if image is large
-        if img.shape[1] > 1000:
-            img = cv2.resize(img, (1000, int(img.shape[0] * 1000 / img.shape[1])))
-
-        # Convert to grayscale and upscale
+        # Convert to grayscale
         gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
-        gray = cv2.resize(gray, None, fx=4, fy=4, interpolation=cv2.INTER_CUBIC)
-        gray = cv2.GaussianBlur(gray, (5, 5), 0)
+
+        # Resize and enhance
+        gray = cv2.resize(gray, None, fx=4, fy=4, interpolation=cv2.INTER_LINEAR)
+        gray = cv2.GaussianBlur(gray, (3, 3), 0)
         gray = cv2.equalizeHist(gray)
 
-        # Thresholding
+        # Threshold
         _, thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
 
-        # Invert if needed
+        # Invert if dark background
         if np.mean(thresh > 127) < 0.5:
             thresh = cv2.bitwise_not(thresh)
 
-        # OCR
-        result = reader.readtext(thresh, detail=0)
-        print("🔍 OCR Text:", result)
-        combined_text = " ".join(result)
+        # OCR using Tesseract
+        config = "--psm 6 -c tessedit_char_whitelist=0123456789."
+        text = pytesseract.image_to_string(thresh, config=config)
+        print("🔍 OCR Text:", text)
 
         # Extract weight
-        match = re.search(r"(\d{1,4}(?:\.\d{1,2})?)", combined_text)
+        match = re.search(r"\d{1,3}(?:\.\d{1,2})?", text)
         if match:
-            weight = match.group(1)
+            weight = match.group()
             return f"{weight} kg", 100.0
         else:
             return "No weight detected kg", 0.0
 
     except Exception as e:
-        print("❌ OCR Error:", e)
         return f"Error: {str(e)}", 0.0