Update app.py

app.py

@@ -60,8 +60,8 @@ demo1 = gr.Interface(
         gr.Image(shape=(32, 32), label="Input Image", value='examples/cat.jpg'),
         gr.Slider(1, 10, value = 3, step=1, label="Number of Top Classes"),
         gr.Checkbox(label="Show GradCAM?", value=True),
-        gr.Slider(-4, -1, value = -1, step=1, label="Which Layer?"),
-        gr.Slider(0, 1, value = 0.7, label="Transparncy", step=0.1)
+        gr.Slider(-4, -1, value = -2, step=1, label="Which Layer?"),
+        gr.Slider(0, 1, value = 0.7, label="Transparency", step=0.1)
     ],
     outputs=[gr.Image(shape=(32, 32), label="Output Image"),
              gr.Label(label='Top Classes')],
@@ -82,10 +82,10 @@ def show_incorrect(num_examples=10, show_cam=True, target_layer=-1, transparency
 demo2 = gr.Interface(
     fn=show_incorrect,
     inputs=[
-        gr.Number(value=10, minimum=1, maximum=len(missed_df), label="No. of missclassified Examples", precision=0),
+        gr.Number(value=20, minimum=1, maximum=len(missed_df), label="No. of missclassified Examples", precision=0),
         gr.Checkbox(label="Show GradCAM?", value=True),
-        gr.Slider(-4, -1, value = -1, step=1, label="Which Layer?"),
-        gr.Slider(0, 1, value = 0.7, label="Transparncy", step=0.1),
+        gr.Slider(-4, -1, value = -2, step=1, label="Which Layer?"),
+        gr.Slider(0, 1, value = 0.7, label="Transparency", step=0.1),
     ],
     outputs=[gr.Gallery(label="Missclassified Images (Truth / Predicted)", columns=4)]
 )