Update app.py

app.py

@@ -41,8 +41,8 @@ def inference(input_image):
         result[categories[top5_catid[i]]] = top5_prob[i].item()
     return result
 
-inputs = gr.inputs.Image(type='pil')
-outputs = gr.outputs.Image(type="confidences",num_top_classes=5)
+inputs = gr.inputs.Image(type='pil', label="Original Image")
+outputs = gr.outputs.Image(type="pil", label="Output Image", num_top_classes=5)
 
 title = "GOOGLENET"
 description = "Gradio demo for GOOGLENET, GoogLeNet was based on a deep convolutional neural network architecture codenamed Inception which won ImageNet 2014. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."