Update ocr_engine.py

ocr_engine.py

@@ -3,47 +3,59 @@ import numpy as np
 import cv2
 import re
 
+# Load OCR engine
 reader = easyocr.Reader(['en'], gpu=False)
 
 def extract_weight_from_image(pil_img):
     try:
         img = np.array(pil_img)
 
-        # No enhancement, just resize
+        # Resize large image if needed
         max_dim = 1000
         height, width = img.shape[:2]
         if max(height, width) > max_dim:
             scale = max_dim / max(height, width)
             img = cv2.resize(img, None, fx=scale, fy=scale, interpolation=cv2.INTER_AREA)
 
+        # OCR without heavy preprocessing
         results = reader.readtext(img)
         print("DEBUG OCR RESULTS:", results)
 
-        if not results:
-            return "No text detected", 0.0, "OCR returned empty list"
-
         raw_texts = []
         weight_candidates = []
 
         for _, text, conf in results:
             original = text
             cleaned = text.lower().strip()
+
+            # Fix common OCR mistakes
             cleaned = cleaned.replace(",", ".")
             cleaned = cleaned.replace("o", "0").replace("O", "0")
             cleaned = cleaned.replace("s", "5").replace("S", "5")
             cleaned = cleaned.replace("g", "9").replace("G", "6")
             cleaned = cleaned.replace("kg", "").replace("kgs", "")
-            cleaned = re.sub(r"[^\d\.]", "", cleaned)
+            cleaned = re.sub(r"[^0-9\.]", "", cleaned)
 
             raw_texts.append(f"{original} → {cleaned} (conf: {round(conf, 2)})")
 
-            if re.fullmatch(r"\d{2,4}(\.\d{1,3})?", cleaned):
+            # Match flexible weight formats like 75.02, 97.2, 102.34
+            if cleaned.count(".") <= 1 and re.match(r"^\d{2,4}(\.\d{1,3})?$", cleaned):
                 weight_candidates.append((cleaned, conf))
 
         if not weight_candidates:
             return "Not detected", 0.0, "\n".join(raw_texts)
 
+        # Get best weight
         best_weight, best_conf = sorted(weight_candidates, key=lambda x: -x[1])[0]
+
+        # Strip unnecessary leading zeros
+        if "." in best_weight:
+            int_part, dec_part = best_weight.split(".")
+            int_part = int_part.lstrip("0") or "0"
+            best_weight = f"{int_part}.{dec_part}"
+        else:
+            best_weight = best_weight.lstrip("0") or "0"
+
         return best_weight, round(best_conf * 100, 2), "\n".join(raw_texts)
 
     except Exception as e: