Create app.py

app.py

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+import gradio as gr
+import numpy as np
+from PIL import Image
+import tensorflow as tf
+import tensorflow_hub as hub
+
+# Load model from TF-Hub
+style_transfer_model = hub.load("https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2")
+
+# function to Stylize the Image or to perform a style transfer
+def do_style_transfer(content_image, style_image):
+    # Convert to float32 numpy array, add batch dimension, and normalize to range [0, 1]. Example using numpy:
+    content_image = tf.convert_to_tensor(content_image, np.float32)[tf.newaxis, ...] / 255.
+    style_image = tf.convert_to_tensor(style_image, np.float32)[tf.newaxis, ...] / 255.
+    # Stylize image
+    output = style_transfer_model(content_image, style_image)
+    stylized_image = output[0]
+    
+    return Image.fromarray(np.uint8(stylized_image[0] * 255))
+
+
+content_image_input = gr.inputs.Image(label="Content Image")
+style_image_input = gr.inputs.Image(shape=(256, 256), label="Style Image")
+
+# Add image examples for users    
+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"]
+
+# Customize interface
+title = "Fast Neural Style Transfer using TF-Hub"
+description = "Demo for Neural Style Transfer using a pretrained Arbitrary 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."
+article = "**References**\n\n"
+          "<a href='https://www.tensorflow.org/hub/tutorials/tf2_arbitrary_image_stylization' target='_blank'> Tutorial to implement Fast Neural Style Transfer using the pretrained model from TensorFlow Hub</a>  \n"
+          "<p style='text-align: center'><a href='https://arxiv.org/abs/1705.06830'>Exploring the structure of a real-time, arbitrary neural artistic stylization network</a></p>"
+          ""
+content_input = gr.inputs.Image(label="Content Image", source="upload")
+style_input = gr.inputs.Image(label="Style Image", source="upload")
+
+app_interface = gr.Interface(fn=do_style_transfer,
+                             inputs=[content_image_input, style_image_input],
+                             outputs="image",
+                             title=title,
+                             description=description,
+                             examples=[glacier, golden_gate, joshua_tree],
+                             article=article
+                            )
+app_interface.launch()