fix gradio input/output issue

app.py

@@ -51,8 +51,8 @@ def inference(input_image):
         result[categories[top5_catid[i]]] = top5_prob[i].item()
     return result
 
-inputs = gr.inputs.Image(type='pil')
-outputs = gr.outputs.Label(type="confidences",num_top_classes=5)
+inputs = gr.Image(type='pil')
+outputs = gr.Label(type="confidences",num_top_classes=5)
 
 title = "SimpleNet"
 description = "Gradio demo for SimpleNet network pre-trained on ImageNet. This demo uses the simplenet_5m_m1 variant. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."