"Example"

app.py

@@ -59,6 +59,8 @@ def classify_image(image):
     # pred = model.predict(img_array)
     # return pred[0][0]
 
+examples=[os.path.join(os.path.dirname(__file__),'7227b3db-c212-4370-8b42-443eea1577aa___RS_Early.B 7306.JPG','7456db33-766c-4a68-b924-ddf69d579981___RS_Early.B 6723.JPG','7486e823-64f7-4e43-ab51-26261b077fc2___RS_Early.B 6785.JPG','8829e413-5a7a-4680-b873-e71dfa9dbfe4___RS_LB 3974.JPG','9001b18c-b659-4c56-9dfb-0d0bf64a7b4a___RS_LB 4987.JPG','9009c86e-1205-4694-b0bb-ef7cf78dd104___RS_LB 3995.JPG','Potato_healthy-76-_0_2420.jpg','Potato_healthy-76-_0_6833.jpg','Potato_healthy-76-_0_7539.jpg')]
+
 # Define the Gradio interface for image input
 input_interface = gr.inputs.Image()
 
@@ -66,4 +68,4 @@ input_interface = gr.inputs.Image()
 output_interface = gr.Textbox()
 
 # Launch the Gradio interface with the classify_image function as the prediction function
-gr.Interface(fn=classify_image, inputs=input_interface, outputs=output_interface).launch()
+gr.Interface(fn=classify_image, inputs=input_interface, outputs=output_interface,Examples=examples).launch()