Update app.py

app.py

@@ -27,12 +27,13 @@ def predict_regression(image):
     top_1_confidence = np.round(float(prediction[0][top_1_idx]), 2)  # Get the confidence score
     return {top_1_label: top_1_confidence}  # Return only the top-1 result
 
-# Create Gradio interface
-input_image = gr.Image()
-output_text = gr.Label()  # Use gr.Label to show top-1 result
+
+#Create Gradio interface
+input_image = gr.inputs.Image()
+output_text = gr.outputs.Label()  # Use gr.Label to show top-1 result
 interface = gr.Interface(fn=predict_regression, 
                          inputs=input_image, 
                          outputs=output_text,  # Change output to Label to display single label and confidence
-                         examples=examples=["images/bond.jpg","images/wolfes.jpg","images/scared-Cat.jpg","images/one-Does-Not-Simply.jpg", "images/cat.jpg", "images/kronk.jpg", "images/zebra.jpg", "images/dog.jpg", "images/johnson.jpg", "images/panda.jpg"],  
+                         examples=["images/bond.jpg","images/wolfes.jpg","images/scared-Cat.jpg","images/one-Does-Not-Simply.jpg", "images/cat.jpg", "images/kronk.jpg", "images/zebra.jpg", "images/dog.jpg", "images/johnson.jpg", "images/panda.jpg"],  
                          description="You ever wonder what your spiritual Animal is? Well here's the answer.")
 interface.launch()