Update app.py

app.py

@@ -33,7 +33,7 @@ inv_normalize = T.Normalize(
     mean=[-0.50/0.23, -0.50/0.23, -0.50/0.23],
     std=[1/0.23, 1/0.23, 1/0.23])
 
-grad_cams = [GradCAM(model=model, target_layers=[model.convblock3[i]], use_cuda=False) for i in range(4)]
+grad_cams = [GradCAM(model=model, target_layers=[model.convblock3[i]], use_cuda=False) for i in range(5)]
 
 def get_gradcam_image(input_tensor, label, target_layer):
     grad_cam = grad_cams[target_layer]
@@ -44,6 +44,7 @@ def get_gradcam_image(input_tensor, label, target_layer):
 
 
 def image_classifier(input_image, top_classes=3, show_cam=True, target_layers=[2, 3], transparency=0.5):
+    global top_classes_g
     orig_image = input_image
     input_image = transform(input_image)
      
@@ -77,7 +78,7 @@ demo1 = gr.Interface(
         gr.Slider(1, 10, value=3, step=1, label="Top Classes",
                   info="How many top classes do you want to view?"),
         gr.Checkbox(label="Enable GradCAM", value=True, info="Do you want to see Class Activation Maps?"),
-        gr.CheckboxGroup(["-4", "-3", "-2", "-1"], value=["-2", "-1"], label="Network Layers", type='index',
+        gr.CheckboxGroup(["-5","-4", "-3", "-2", "-1"], value=["-2", "-1"], label="Network Layers", type='index',
                          info="Which layer CAMs do you want to visualize?",),
         gr.Slider(0, 1, value=0.5, label="Transparency", step=0.1,
                   info="Set Transparency of CAMs")