Update app.py

app.py

@@ -28,6 +28,9 @@ def predict(pilimg):
     source = pilimg
     # x = np.asarray(pilimg)
     # print(x.shape)
+
+    detection_model = YOLO(best_yolo_model, task='detect')# load the model
+
     result = detection_model.predict(source, conf=0.4, iou=0.6) # confidence threshold, intersection over union threshold
     
     #print("Result: ", result)
@@ -40,7 +43,7 @@ def predict(pilimg):
         return out_pilimg
 
 REPO_ID = "ITI107-2024S2/8035531F"  # The repo ID of the model
-detection_model = load_model(REPO_ID)
+#detection_model = load_model(REPO_ID)
 
 title = "Detect Durian and Mangosteen (King and Queen of Fruits) In The Image"
 interface = gr.Interface(