Update app.py

app.py

@@ -22,7 +22,7 @@ classes = ('plane', 'car', 'bird', 'cat', 'deer',
 model_layer_names = ["1", "2", "3"]
 
 def get_layer(layer_name):
-    print(layer_name)
+    print("layer name:", layer_name)
     if layer_name == 1:
         return [model.layer1[-1]]
     elif layer_name == 2:
@@ -72,7 +72,7 @@ def inference(input_img, show_gradcam, layer_name, num_classes, transparancy = 0
 
     if show_gradcam:
         target_layers = get_layer(layer_name)
-        print(target_layers)
+        print("target layer",target_layers)
         cam = GradCAM(model=model, target_layers=target_layers)
         grayscale_cam = cam(input_tensor= input_img)
         grayscale_cam = grayscale_cam[0, :]
@@ -100,8 +100,7 @@ demo = gr.Interface(
     ],
     title = "CIFAR 10 trained on ResNet model in pytorch lightning with Gradcam",
     description = " A simple gradio inference to infer on resnet18 model",
-    examples = [["cat.jpg", 1, True, 10, 0.4],
-                ["dog.jpg", 1, False,  4, 1]]
+    examples = [["cat.jpg", 1, True, 10, 0.4]]
 )
 
 if __name__ == "__main__":