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app.py

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+import streamlit as st
+from transformers import pipeline
+from PIL import Image
+import numpy as np
+import tensorflow as tf
+import tensorflow_hub as hub
+
+st.title("Fast Neural image style transfer")
+st.write("Streamlit demo for Fast arbitrary image style transfer using a pretrained Image Stylization model from TensorFlow Hub. To use it, simply upload a content image and style image. To learn more about the project, please find the references listed below.")
+
+# Load image stylization module.
+@st.cache(allow_output_mutation=True)
+def load_model():
+  return hub.load("https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2")
+
+style_transfer_model = load_model()
+
+def perform_style_transfer(content_image, style_image):
+  # Convert to float32 numpy array, add batch dimension, and normalize to range [0, 1]
+    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.
+    
+    output = style_transfer_model(content_image, style_image)
+    stylized_image = output[0]
+    
+    return Image.fromarray(np.uint8(stylized_image[0] * 255))
+
+# Upload content and style images.
+content_image = st.file_uploader("Upload a content image")
+style_image = st.file_uploader("Upload a style image")
+
+# default images
+st.write("Or you can choose from the following examples")
+col1, col2, col3 = st.columns(3)
+
+if col2.button("Joshua Tree"):
+  content_image = "joshua_tree.jpeg"
+  style_image = "starry_night.jpeg"
+
+
+
+if style_image and content_image is not None:
+  col1, col2 = st.columns(2)
+
+  content_image = Image.open(content_image)
+  # It is recommended that the style image is about 256 pixels (this size was used when training the style transfer network).
+  style_image = Image.open(style_image).resize((256, 256))
+
+  output_image=perform_style_transfer(content_image, style_image)
+
+  col1.header("Content Image")
+  col1.image(content_image, use_column_width=True)
+  col2.header("Style Image")
+  col2.image(style_image, use_column_width=True)
+
+  st.header("Output: Style transfer Image")
+  st.image(output_image, use_column_width=True)
+
+# scroll down to see the references
+st.markdown("**References**")
+st.markdown("<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", unsafe_allow_html=True)
+st.markdown("<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>", unsafe_allow_html=True)

requirements.txt

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+numpy==1.21.2
+tensorflow==2.11.0
+tensorflow_hub==0.12.0