Update app.py

app.py

@@ -85,12 +85,27 @@ def detect_image(image, model_choice, conf_threshold):
         classes = r.boxes.cls.cpu().numpy()
         for i, (box, cls) in enumerate(zip(boxes, classes)):
             label = CLASS_NAMES[int(cls)]
-            counts[label] +=1
-            rows.append([i+1,label])
-            x1,y1,x2,y2 = map(int, box)
+            counts[label] += 1
+            rows.append([i+1, label])
+        
+            x1, y1, x2, y2 = map(int, box)
             color = (0,255,0) if label=="RBC" else (255,0,0) if label=="WBC" else (0,0,255)
-            cv2.rectangle(img,(x1,y1),(x2,y2),color,2)
-            cv2.putText(img,label,(x1,y1-5),cv2.FONT_HERSHEY_SIMPLEX,0.5,color,2)
+        
+            # Draw box
+            cv2.rectangle(img, (x1,y1), (x2,y2), color, 2)
+        
+            # Draw numbered label
+            text = f"{i+1}: {label}"
+            cv2.putText(
+                img,
+                text,
+                (x1, y1 - 8),
+                cv2.FONT_HERSHEY_SIMPLEX,
+                0.6,
+                color,
+                2,
+                cv2.LINE_AA
+            )
 
     df = pd.DataFrame(rows, columns=["Object_No","Class"])
     csv_file = tempfile.NamedTemporaryFile(delete=False, suffix=".csv")