Create app.py

app.py

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+import os
+import tensorflow as tf
+os.environ['TFHUB_MODEL_LOAD_FORMAT'] = 'COMPRESSED'
+import numpy as np
+import PIL.Image
+import gradio as gr
+import tensorflow_hub as hub
+import matplotlib.pyplot as plt
+from real_esrgan_app import *
+
+'''
+inference(img,mode)
+'''
+
+hub_module = hub.load('https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2')
+
+def tensor_to_image(tensor):
+    tensor = tensor*255
+    tensor = np.array(tensor, dtype=np.uint8)
+    if np.ndim(tensor)>3:
+      assert tensor.shape[0] == 1
+      tensor = tensor[0]
+    return PIL.Image.fromarray(tensor)
+
+
+style_urls = {
+    'Kanagawa great wave': 'The_Great_Wave_off_Kanagawa.jpg',
+    'Kandinsky composition 7': 'Kandinsky_Composition_7.jpg',
+    'Hubble pillars of creation': 'Pillars_of_creation_2014_HST_WFC3-UVIS_full-res_denoised.jpg',
+    'Van gogh starry night': 'Van_Gogh_-_Starry_Night_-_Google_Art_Project.jpg',
+    'Turner nantes': 'JMW_Turner_-_Nantes_from_the_Ile_Feydeau.jpg',
+    'Munch scream': 'Edvard_Munch.jpg',
+    'Picasso demoiselles avignon': 'Les_Demoiselles.jpg',
+    'Picasso violin': 'picaso_violin.jpg',
+    'Picasso bottle of rum': 'picaso_rum.jpg',
+    'Fire': 'Large_bonfire.jpg',
+    'Derkovits woman head': 'Derkovits_Gyula_Woman_head_1922.jpg',
+    'Amadeo style life': 'Amadeo_Souza_Cardoso.jpg',
+    'Derkovtis talig': 'Derkovits_Gyula_Talig.jpg',
+    'Kadishman': 'kadishman.jpeg'
+}
+
+
+style_images = [k for k, v in style_urls.items()]
+
+def image_click(images, evt: gr.SelectData,
+    ):
+    img_selected = images[evt.index]["name"]
+    #print(img_selected)
+    return img_selected
+
+
+#radio_style = gr.Radio(style_images, label="Choose Style")
+
+def perform_neural_transfer(content_image_input, style_image_input, super_resolution_type, hub_module = hub_module):
+    content_image = content_image_input.astype(np.float32)[np.newaxis, ...] / 255.
+    content_image = tf.image.resize(content_image, (400, 600))
+
+    #style_image_input = style_urls[style_image_input]
+    #style_image_input = plt.imread(style_image_input)
+    style_image = style_image_input.astype(np.float32)[np.newaxis, ...] / 255.
+
+    style_image = tf.image.resize(style_image, (256, 256))
+
+    outputs = hub_module(tf.constant(content_image), tf.constant(style_image))
+    stylized_image = outputs[0]
+
+    stylized_image = tensor_to_image(stylized_image)
+    content_image_input = tensor_to_image(content_image_input)
+    stylized_image = stylized_image.resize(content_image_input.size)
+    if super_resolution_type is "none":
+        return stylized_image
+    else:
+        stylized_image = inference(stylized_image, super_resolution_type)
+        return stylized_image
+
+with gr.Blocks() as demo:
+    gr.HTML("<h1><center> 🐑 Art Generation with Neural Style Transfer </center></h1>")
+
+    with gr.Row():
+        style_reference_input_gallery = gr.Gallery(list(style_urls.values()),
+                        #width = 512,
+                        height = 768 + 32,
+                        label = "Style Image gallery (click to use)")
+        with gr.Column():
+            super_resolution_type = gr.Radio(["none" ,"base", "anime"], type="value", default="none", label="model used to super resolution the Image Transformed")
+            style_reference_input_image = gr.Image(
+                        label = "Style Image (you can upload yourself or click from left gallery)",
+                        #width = 512,
+                        interactive = True, value = style_urls["Kanagawa great wave"]
+                        )
+            content_image_input = gr.Image(label="Content Image", interactive = True,
+                        #width = 512
+                    )
+            trans_image_output = gr.Image(label="Image Transformed", interactive = True,
+                    #width = 512
+            )
+            trans_button = gr.Button(label = "transform Content image style from Style Image")
+
+
+    style_reference_input_gallery.select(
+        image_click, style_reference_input_gallery, style_reference_input_image
+    )
+
+    trans_button.click(perform_neural_transfer, [content_image_input, style_reference_input_image], trans_image_output)
+
+    gr.Examples(
+        [
+        [style_urls["Kanagawa great wave"], style_urls["Kadishman"]],
+        [style_urls["Derkovits woman head"], style_urls["Kadishman"]],
+        ],
+        inputs = [style_reference_input_image, content_image_input],
+        label = "Transform Examples"
+    )
+
+demo.launch()