Update app.py

app.py

@@ -67,9 +67,9 @@ def predict(img) -> Tuple[Dict, float]:
 ### 4. Gradio app ###
 
 # Create title, description and article strings
-title = "DeepFundus 👀"
-description = "A ResNet50 feature extractor computer vision model to classify funduscopic images."
-article = "Created with the help from [09. PyTorch Model Deployment](https://www.learnpytorch.io/09_pytorch_model_deployment/)."
+#title = "DeepFundus 👀"
+#description = "A ResNet50 feature extractor computer vision model to classify funduscopic images."
+#article = "Created with the help from [09. PyTorch Model Deployment](https://www.learnpytorch.io/09_pytorch_model_deployment/)."
 
 # Create examples list from "examples/" directory
 example_list = [["examples/" + example] for example in os.listdir("examples")]
@@ -80,10 +80,10 @@ demo = gr.Interface(fn=predict, # mapping function from input to output
                     outputs=[gr.Label(num_top_classes=3, label="Predictions"), # what are the outputs?
                              gr.Number(label="Prediction time (s)")], # our fn has two outputs, therefore we have two outputs
                     # Create examples list from "examples/" directory
-                    examples=example_list, 
-                    title=title,
-                    description=description,
-                    article=article)
+                    examples=example_list) 
+                    #title=title,
+                    #description=description,
+                    #article=article)
 
 # Launch the demo!
 demo.launch()