Update ocr_engine.py

ocr_engine.py

@@ -3,18 +3,16 @@ import re
 import cv2
 from PIL import Image
 import easyocr
-import os
 
-# ✅ Initialize OCR reader only once
+# ✅ Initialize EasyOCR Reader once
 reader = easyocr.Reader(['en'], gpu=False)
 
 def preprocess_image(image):
     """
-    Preprocess the image to improve OCR detection.
-    Converts to grayscale and applies adaptive threshold.
+    Convert to grayscale and apply adaptive thresholding
+    to enhance contrast for digital scale OCR.
     """
     gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
-    # Apply adaptive threshold to isolate digits better
     thresh = cv2.adaptiveThreshold(
         gray, 255,
         cv2.ADAPTIVE_THRESH_MEAN_C,
@@ -25,43 +23,34 @@ def preprocess_image(image):
 
 def extract_weight_from_image(pil_image):
     try:
-        # ✅ Step 1: Convert to OpenCV format
+        # ✅ Convert PIL image to OpenCV format
         image = np.array(pil_image.convert("RGB"))
 
-        # ✅ Step 2: Preprocess image
+        # ✅ Preprocess image
         processed = preprocess_image(image)
 
-        # ✅ Step 3: Optional - Save debug image
+        # ✅ Optional: Save debug image for troubleshooting
         debug_path = "debug_processed_image.png"
         Image.fromarray(processed).save(debug_path)
-        print(f"[DEBUG] Saved preprocessed image to {debug_path}")
+        print(f"[DEBUG] Preprocessed image saved to: {debug_path}")
 
-        # ✅ Step 4: Run EasyOCR
+        # ✅ Perform OCR using EasyOCR
         result = reader.readtext(processed)
 
         print("🔍 OCR Results:")
-        for r in result:
-            print(f"  • Text: '{r[1]}' | Confidence: {r[2]*100:.2f}%")
-
-        # ✅ Step 5: Look for a decimal number like 53.25
-        weight = None
-        confidence = 0.0
+        for detection in result:
+            print(f"  • Text: '{detection[1]}' | Confidence: {detection[2]*100:.2f}%")
 
+        # ✅ Extract first matching numeric value
         for detection in result:
-            text = detection[1].replace(",", ".")  # Handle comma decimal (if any)
+            text = detection[1].replace(",", ".")  # normalize decimal
             conf = detection[2]
-
-            # Look for numbers like 53.25 or 100
-            match = re.search(r"\b\d{1,3}(\.\d{1,2})?\b", text)
+            match = re.search(r"\b\d{1,4}(\.\d{1,2})?\b", text)
             if match:
-                weight = match.group()
-                confidence = conf
-                break
+                return match.group(), round(conf * 100, 2)
 
-        if weight:
-            return weight, round(confidence * 100, 2)
-        else:
-            return "No weight detected", 0.0
+        # ❌ No weight found
+        return "No weight detected", 0.0
 
     except Exception as e:
         print(f"❌ OCR Error: {e}")