Delete super_resolution_style_trans_app.py

super_resolution_style_trans_app.py

@@ -1,126 +0,0 @@
-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)
-
-    print("super_resolution_type :")
-    print(super_resolution_type)
-    #print(super_resolution_type.value)
-    
-    if super_resolution_type not in ["base", "anime"]:
-        return stylized_image
-    else:
-        print("call 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 Fixed by Real-ESRGAN </center></h1>")
-
-    with gr.Row():
-        style_reference_input_gallery = gr.Gallery(list(style_urls.values()),
-                        #width = 512,
-                        height = 768 + 128,
-                        label = "Style Image gallery (click to use)")
-        with gr.Column():
-            #super_resolution_type = gr.Radio(["base", "anime", "none"], type="value", default="base", label="choose Real-ESRGAN model type used to super resolution the Image Transformed")
-            super_resolution_type = gr.Radio(choices = ["base", "anime", "none"],
-                        value="base", label="choose Real-ESRGAN model type used to super resolution the Image Transformed", 
-                                                 interactive = True)
-            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, super_resolution_type], trans_image_output)
-
-    gr.Examples(
-        [
-        [style_urls["Kanagawa great wave"], style_urls["Kadishman"], "none"],
-        [style_urls["Derkovits woman head"], style_urls["Kadishman"], "base"],
-        [style_urls["Kadishman"], style_urls["Kadishman"], "anime"],
-        ],
-        inputs = [style_reference_input_image, content_image_input, super_resolution_type],
-        label = "Transform Examples"
-    )
-
-demo.launch()