Update app.py

app.py

@@ -20,10 +20,18 @@ def perform_style_transfer(content_image, style_image):
 content_image_input = gr.inputs.Image(label="Content Image")
 style_image_input = gr.inputs.Image(shape=(256, 256), label="Style Image")
 
+# Examples
+golden_gate = ["golden_gate_bridge.jpeg", "the_great_wave.jpeg"]
+joshua_tree = ["joshua_tree.jpeg", "starry_night.jpeg"]
+glacier = ["glacier_national_park.jpeg", "the_scream.jpg"]
 
 app_interface = gr.Interface(fn=perform_style_transfer,
                              inputs=[content_image_input, style_image_input],
                              outputs="image",
                              title="Fast Neural Style Transfer",
-                             description="Gradio demo for Fast Neural Style Transfer using a pretrained Image Stylization model from TensorFlow Hub. To use it, simply upload a content image and style image, or click one of the examples to load them. To learn more about the project, please find the references listed below.")
+                             description="Gradio demo for Fast Neural Style Transfer using a pretrained Image Stylization model from TensorFlow Hub. To use it, simply upload a content image and style image, or click one of the examples to load them. To learn more about the project, please find the references listed below.",
+                             examples=[glacier, golden_gate, joshua_tree],
+                             article="**References**\n\n"
+                             "<a href='https://www.tensorflow.org/hub/tutorials/tf2_arbitrary_image_stylization' target='_blank'>1. Tutorial to implement Fast Neural Style Transfer using the pretrained model from TensorFlow Hub</a>  \n"
+                             "<a href='https://huggingface.co/spaces/luca-martial/neural-style-transfer' target='_blank'>2. The idea to build a neural style transfer application was inspired from this Hugging Face Space </a>")
 app_interface.launch()