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app.py

@@ -1,7 +1,6 @@
 import gradio as gr
 import tensorflow as tf
 import numpy as np
-from PIL import Image
 
 # Load the saved model
 model = tf.keras.models.load_model('mymodel.h5')
@@ -26,11 +25,11 @@ def classify_image(image):
     return predicted_class
 
 # Define the Gradio interface
-image_input = gr.Image(type="pil", label="Upload Image")
-label_output = gr.Label()
+image_input = gr.inputs.Image(type="pil", label="Upload Image")
+label_output = gr.outputs.Label()
 
 # Create the Gradio interface
 interface = gr.Interface(fn=classify_image, inputs=image_input, outputs=label_output, title="Image Classifier")
 
 # Launch the interface
-interface.launch()
+interface.launch()