Update app.py

app.py

@@ -7,7 +7,7 @@ model_path = "Cat_transfer_learning_MobileNetV2.keras"
 model = tf.keras.models.load_model(model_path)
 
 # Define the core prediction function
-def predict_dog(image):
+def predict_cat(image):
     # Preprocess image
     print(type(image))
     image = Image.fromarray(image.astype('uint8'))  # Convert numpy array to PIL image
@@ -36,7 +36,7 @@ def predict_dog(image):
 # Create the Gradio interface
 input_image = gr.Image()
 iface = gr.Interface(
-    fn=predict_dog,
+    fn=predict_cat,
     inputs=input_image,
     outputs=gr.Label(),
     examples=["images/americanshorthair_1.jpg", "images/americanshorthair_2.jpg", "images/americanshorthair_3.jpg", "images/bengal_1.jpg", "images/bengal_2.jpeg", "images/bengal_3.jpg", "images/mainecoon_1.jpg", "images/mainecoon_2.jpeg", "images/mainecoon_3.jpg", "images/ragdoll_1.jpg", "images/ragdoll_2.jpg", "images/ragdoll_3.jpeg", "images/scottishfold_1.jpeg", "images/scottishfold_2.jpg", "images/scottishfold_3.jpg", "images/sphinx_1.jpg", "images/sphinx_2.jpg", "images/sphinx_3.jpg"],