Upload app.py

app.py

@@ -64,7 +64,7 @@ def predict(img) -> Tuple[Dict, float]:
 ### 4. Gradio app ###
 
 # Create title, description and article strings
-title = "Retinal Disease Detection"
+#title = "Retinal Disease Detection"
 #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/)."
 
@@ -77,7 +77,7 @@ demo = gr.Interface(fn=predict, # mapping function from input to output
                     outputs=[gr.Label(num_top_classes=4, 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
-                    title=title,
+                    #title=title,
                     examples=example_list,
                     css="""
                     .gradio-container {background-color: #0B0F19}