Duplicate from nightfury/Neural_Style_Transfer

Co-authored-by: spartan <nightfury@users.noreply.huggingface.co>

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README.md

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+---
+title: Neural Style Transfer
+emoji: 💻
+colorFrom: gray
+colorTo: green
+sdk: gradio
+app_file: app.py
+pinned: false
+license: mit
+duplicated_from: nightfury/Neural_Style_Transfer
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+# Configuration
+`title`: _string_  
+Display title for the Space
+`emoji`: _string_  
+Space emoji (emoji-only character allowed)
+`colorFrom`: _string_  
+Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
+`colorTo`: _string_  
+Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
+`sdk`: _string_  
+Can be either `gradio` or `streamlit`
+`sdk_version` : _string_  
+Only applicable for `streamlit` SDK.  
+See [doc](https://hf.co/docs/hub/spaces) for more info on supported versions.
+
+`app_file`: _string_  
+Path to your main application file (which contains either `gradio` or `streamlit` Python code).  
+Path is relative to the root of the repository.
+
+`pinned`: _boolean_  
+Whether the Space stays on top of your list.
+

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 = ["example_deadpool2.jpeg", "style_the_great_wave.jpeg"]
+joshua_tree = ["example_deadpool.png", "style_starry_night.jpeg"]
+avatar = ["example_avatar.jpeg", "style_the_scream.jpg"]
+joker = ["example_joker.jpeg", "style_polasticot1.jpeg"]
+einstein = ["example_einstein.jpeg", "style_polasticot2.jpeg"]
+monalisa = ["example_mona1.jpeg", "style_polasticot3.jpeg"]
+paris = ["example_paris.jpeg", "style_vangogh.jpeg"]
+
+# Customize interface
+title = "Fast Neural Style Transfer using TF-Hub"
+description = "<p style='text-align: center'> 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.</p>"
+article = r"""<b>:: References ::</b>
+<br>
+<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>
+<br>
+<a href='https://arxiv.org/abs/1705.06830'>
+Exploring the structure of a real-time, arbitrary neural artistic stylization network
+</a>
+<br>
+<center><img src='https://visitor-badge.glitch.me/badge?page_id=dj_arbi_img_stylization' alt='visitor badge'></center>
+"""
+
+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=[golden_gate,joshua_tree,avatar,joker,einstein,monalisa,paris],
+                             article=article
+                            )
+app_interface.launch()

requirements.txt

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+matplotlib
+numpy==1.21.2
+tensorflow==2.2.0
+tensorflow_hub==0.12.0