Update ocr_engine.py

ocr_engine.py

@@ -5,36 +5,24 @@ import re
 
 reader = easyocr.Reader(['en'], gpu=False)
 
-def enhance_image(img):
-    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)
-
-    gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
-    gray = cv2.fastNlMeansDenoising(gray, h=15)
-
-    kernel = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]])
-    sharp = cv2.filter2D(gray, -1, kernel)
-
-    clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8))
-    enhanced = clahe.apply(sharp)
-
-    return enhanced
-
 def extract_weight_from_image(pil_img):
     try:
         img = np.array(pil_img)
-        enhanced = enhance_image(img)
 
-        results = reader.readtext(enhanced)
+        # No enhancement, just resize
+        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)
+
+        results = reader.readtext(img)
         print("DEBUG OCR RESULTS:", results)
 
         if not results:
             return "No text detected", 0.0, "OCR returned empty list"
 
-        all_texts = []
+        raw_texts = []
         weight_candidates = []
 
         for _, text, conf in results:
@@ -47,24 +35,16 @@ def extract_weight_from_image(pil_img):
             cleaned = cleaned.replace("kg", "").replace("kgs", "")
             cleaned = re.sub(r"[^\d\.]", "", cleaned)
 
-            all_texts.append(f"{original} → {cleaned} (conf: {round(conf, 2)})")
+            raw_texts.append(f"{original} → {cleaned} (conf: {round(conf, 2)})")
 
             if re.fullmatch(r"\d{2,4}(\.\d{1,3})?", cleaned):
                 weight_candidates.append((cleaned, conf))
 
         if not weight_candidates:
-            return "Not detected", 0.0, "\n".join(all_texts)
+            return "Not detected", 0.0, "\n".join(raw_texts)
 
         best_weight, best_conf = sorted(weight_candidates, key=lambda x: -x[1])[0]
-
-        if "." in best_weight:
-            parts = best_weight.split(".")
-            parts[0] = parts[0].lstrip("0") or "0"
-            best_weight = ".".join(parts)
-        else:
-            best_weight = best_weight.lstrip("0") or "0"
-
-        return best_weight, round(best_conf * 100, 2), "\n".join(all_texts)
+        return best_weight, round(best_conf * 100, 2), "\n".join(raw_texts)
 
     except Exception as e:
         return f"Error: {str(e)}", 0.0, "OCR failed"