Create app.py

app.py

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+import numpy as np
+import tensorflow as tf
+import tensorflow_hub as hub
+import matplotlib.pyplot as plt
+import gradio as gr
+from tensorflow.keras.preprocessing import image
+from PIL import Image
+
+def style_transfer(content_image, style_image):
+  # content_image = plt.imread(content_image)
+  # style_image = plt.imread(style_image)
+  content_image = content_image.astype(np.float32)[np.newaxis, ...] / 255.
+  style_image = style_image.astype(np.float32)[np.newaxis, ...] / 255.
+  try:
+    hub_module = hub.load('https://www.kaggle.com/models/google/arbitrary-image-stylization-v1/TensorFlow1/256/2')
+  except OSError:
+    print("Downloading pre-trained model...")
+    hub_module = tf.saved_model.load('https://tfhub.dev/google/arbitrary-image-stylization-v1/256')
+  outputs = hub_module(tf.constant(content_image), tf.constant(style_image))
+  stylized_image = outputs[0].numpy()
+  stylized_image = stylized_image[0] * 255.
+  stylized_image = stylized_image.astype(np.uint8)
+  stylized_image = Image.fromarray(stylized_image)
+  return stylized_image
+
+interface = gr.Interface(
+    fn=style_transfer,
+    inputs=[
+        gr.Image(label="Content Image (Upload your photo)"),
+        gr.Image(label="Style Image (Choose an artistic style)"),
+    ],
+    outputs="image",
+    title="Style Transfer App",
+    description="Apply artistic styles to your photos using deep learning!",
+)
+interface.launch(debug=True)
+