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magenta と次の発表のモデルコードに基づきます。
Exploring the structure of a real-time, arbitrary neural artistic stylization network. Golnaz Ghiasi, Honglak Lee, Manjunath Kudlur, Vincent Dumoulin, Jonathon Shlens, Proceedings of the British Machine Vision Conference (BMVC), 2017.
セットアップ
はじめに、TF-2 とすべての関連する依存ファイルをインポートしましょう。
import functools
import os
from matplotlib import gridspec
import matplotlib.pylab as plt
import numpy as np
import tensorflow as tf
import tensorflow_hub as hub
print("TF Version: ", tf.__version__)
print("TF Hub version: ", hub.__version__)
print("Eager mode enabled: ", tf.executing_eagerly())
print("GPU available: ", tf.config.list_physical_devices('GPU'))
2024-01-11 18:39:34.938893: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered 2024-01-11 18:39:34.938934: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered 2024-01-11 18:39:34.940506: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered TF Version: 2.15.0 TF Hub version: 0.15.0 Eager mode enabled: True GPU available: [PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU'), PhysicalDevice(name='/physical_device:GPU:1', device_type='GPU'), PhysicalDevice(name='/physical_device:GPU:2', device_type='GPU'), PhysicalDevice(name='/physical_device:GPU:3', device_type='GPU')]
# @title Define image loading and visualization functions { display-mode: "form" }
def crop_center(image):
"""Returns a cropped square image."""
shape = image.shape
new_shape = min(shape[1], shape[2])
offset_y = max(shape[1] - shape[2], 0) // 2
offset_x = max(shape[2] - shape[1], 0) // 2
image = tf.image.crop_to_bounding_box(
image, offset_y, offset_x, new_shape, new_shape)
return image
@functools.lru_cache(maxsize=None)
def load_image(image_url, image_size=(256, 256), preserve_aspect_ratio=True):
"""Loads and preprocesses images."""
# Cache image file locally.
image_path = tf.keras.utils.get_file(os.path.basename(image_url)[-128:], image_url)
# Load and convert to float32 numpy array, add batch dimension, and normalize to range [0, 1].
img = tf.io.decode_image(
tf.io.read_file(image_path),
channels=3, dtype=tf.float32)[tf.newaxis, ...]
img = crop_center(img)
img = tf.image.resize(img, image_size, preserve_aspect_ratio=True)
return img
def show_n(images, titles=('',)):
n = len(images)
image_sizes = [image.shape[1] for image in images]
w = (image_sizes[0] * 6) // 320
plt.figure(figsize=(w * n, w))
gs = gridspec.GridSpec(1, n, width_ratios=image_sizes)
for i in range(n):
plt.subplot(gs[i])
plt.imshow(images[i][0], aspect='equal')
plt.axis('off')
plt.title(titles[i] if len(titles) > i else '')
plt.show()
使用する画像を取得しましょう。
# @title Load example images { display-mode: "form" }
content_image_url = 'https://upload.wikimedia.org/wikipedia/commons/thumb/f/fd/Golden_Gate_Bridge_from_Battery_Spencer.jpg/640px-Golden_Gate_Bridge_from_Battery_Spencer.jpg' # @param {type:"string"}
style_image_url = 'https://upload.wikimedia.org/wikipedia/commons/0/0a/The_Great_Wave_off_Kanagawa.jpg' # @param {type:"string"}
output_image_size = 384 # @param {type:"integer"}
# The content image size can be arbitrary.
content_img_size = (output_image_size, output_image_size)
# The style prediction model was trained with image size 256 and it's the
# recommended image size for the style image (though, other sizes work as
# well but will lead to different results).
style_img_size = (256, 256) # Recommended to keep it at 256.
content_image = load_image(content_image_url, content_img_size)
style_image = load_image(style_image_url, style_img_size)
style_image = tf.nn.avg_pool(style_image, ksize=[3,3], strides=[1,1], padding='SAME')
show_n([content_image, style_image], ['Content image', 'Style image'])
Downloading data from https://upload.wikimedia.org/wikipedia/commons/thumb/f/fd/Golden_Gate_Bridge_from_Battery_Spencer.jpg/640px-Golden_Gate_Bridge_from_Battery_Spencer.jpg 71918/71918 [==============================] - 0s 1us/step Downloading data from https://upload.wikimedia.org/wikipedia/commons/0/0a/The_Great_Wave_off_Kanagawa.jpg 2684586/2684586 [==============================] - 0s 0us/step
TF Hub モジュールをインポートする
# Load TF Hub module.
hub_handle = 'https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2'
hub_module = hub.load(hub_handle)
画風に使用する Hub モジュールのシグネチャは、次のとおりです。
outputs = hub_module(content_image, style_image)
stylized_image = outputs[0]
上記の content_image、style_image、および stylized_image は、形状 [batch_size, image_height, image_width, 3] の 4-D テンソルです。
現在の例では 1 つの画像のみを提供するためバッチの次元は 1 ですが、同じモジュールを使用して、同時に複数の画像を処理することができます。
画像の入力と出力の値範囲は [0, 1] です。
コンテンツとスタイル画像の形状が一致する必要はありません。出力画像の形状はコンテンツ画像の形状と同一です。
画風の実演
# Stylize content image with given style image.
# This is pretty fast within a few milliseconds on a GPU.
outputs = hub_module(tf.constant(content_image), tf.constant(style_image))
stylized_image = outputs[0]
# Visualize input images and the generated stylized image.
show_n([content_image, style_image, stylized_image], titles=['Original content image', 'Style image', 'Stylized image'])
複数の画像で試してみる
# @title To Run: Load more images { display-mode: "form" }
content_urls = dict(
sea_turtle='https://upload.wikimedia.org/wikipedia/commons/d/d7/Green_Sea_Turtle_grazing_seagrass.jpg',
tuebingen='https://upload.wikimedia.org/wikipedia/commons/0/00/Tuebingen_Neckarfront.jpg',
grace_hopper='https://storage.googleapis.com/download.tensorflow.org/example_images/grace_hopper.jpg',
)
style_urls = dict(
kanagawa_great_wave='https://upload.wikimedia.org/wikipedia/commons/0/0a/The_Great_Wave_off_Kanagawa.jpg',
kandinsky_composition_7='https://upload.wikimedia.org/wikipedia/commons/b/b4/Vassily_Kandinsky%2C_1913_-_Composition_7.jpg',
hubble_pillars_of_creation='https://upload.wikimedia.org/wikipedia/commons/6/68/Pillars_of_creation_2014_HST_WFC3-UVIS_full-res_denoised.jpg',
van_gogh_starry_night='https://upload.wikimedia.org/wikipedia/commons/thumb/e/ea/Van_Gogh_-_Starry_Night_-_Google_Art_Project.jpg/1024px-Van_Gogh_-_Starry_Night_-_Google_Art_Project.jpg',
turner_nantes='https://upload.wikimedia.org/wikipedia/commons/b/b7/JMW_Turner_-_Nantes_from_the_Ile_Feydeau.jpg',
munch_scream='https://upload.wikimedia.org/wikipedia/commons/c/c5/Edvard_Munch%2C_1893%2C_The_Scream%2C_oil%2C_tempera_and_pastel_on_cardboard%2C_91_x_73_cm%2C_National_Gallery_of_Norway.jpg',
picasso_demoiselles_avignon='https://upload.wikimedia.org/wikipedia/en/4/4c/Les_Demoiselles_d%27Avignon.jpg',
picasso_violin='https://upload.wikimedia.org/wikipedia/en/3/3c/Pablo_Picasso%2C_1911-12%2C_Violon_%28Violin%29%2C_oil_on_canvas%2C_Kr%C3%B6ller-M%C3%BCller_Museum%2C_Otterlo%2C_Netherlands.jpg',
picasso_bottle_of_rum='https://upload.wikimedia.org/wikipedia/en/7/7f/Pablo_Picasso%2C_1911%2C_Still_Life_with_a_Bottle_of_Rum%2C_oil_on_canvas%2C_61.3_x_50.5_cm%2C_Metropolitan_Museum_of_Art%2C_New_York.jpg',
fire='https://upload.wikimedia.org/wikipedia/commons/3/36/Large_bonfire.jpg',
derkovits_woman_head='https://upload.wikimedia.org/wikipedia/commons/0/0d/Derkovits_Gyula_Woman_head_1922.jpg',
amadeo_style_life='https://upload.wikimedia.org/wikipedia/commons/8/8e/Untitled_%28Still_life%29_%281913%29_-_Amadeo_Souza-Cardoso_%281887-1918%29_%2817385824283%29.jpg',
derkovtis_talig='https://upload.wikimedia.org/wikipedia/commons/3/37/Derkovits_Gyula_Talig%C3%A1s_1920.jpg',
amadeo_cardoso='https://upload.wikimedia.org/wikipedia/commons/7/7d/Amadeo_de_Souza-Cardoso%2C_1915_-_Landscape_with_black_figure.jpg'
)
content_image_size = 384
style_image_size = 256
content_images = {k: load_image(v, (content_image_size, content_image_size)) for k, v in content_urls.items()}
style_images = {k: load_image(v, (style_image_size, style_image_size)) for k, v in style_urls.items()}
style_images = {k: tf.nn.avg_pool(style_image, ksize=[3,3], strides=[1,1], padding='SAME') for k, style_image in style_images.items()}
Downloading data from https://upload.wikimedia.org/wikipedia/commons/d/d7/Green_Sea_Turtle_grazing_seagrass.jpg 3170828/3170828 [==============================] - 0s 0us/step Downloading data from https://upload.wikimedia.org/wikipedia/commons/0/00/Tuebingen_Neckarfront.jpg 406531/406531 [==============================] - 0s 0us/step Downloading data from https://storage.googleapis.com/download.tensorflow.org/example_images/grace_hopper.jpg 61306/61306 [==============================] - 0s 0us/step Downloading data from https://upload.wikimedia.org/wikipedia/commons/b/b4/Vassily_Kandinsky%2C_1913_-_Composition_7.jpg 195196/195196 [==============================] - 0s 0us/step Downloading data from https://upload.wikimedia.org/wikipedia/commons/6/68/Pillars_of_creation_2014_HST_WFC3-UVIS_full-res_denoised.jpg 46930988/46930988 [==============================] - 2s 0us/step Downloading data from https://upload.wikimedia.org/wikipedia/commons/thumb/e/ea/Van_Gogh_-_Starry_Night_-_Google_Art_Project.jpg/1024px-Van_Gogh_-_Starry_Night_-_Google_Art_Project.jpg 397382/397382 [==============================] - 0s 0us/step Downloading data from https://upload.wikimedia.org/wikipedia/commons/b/b7/JMW_Turner_-_Nantes_from_the_Ile_Feydeau.jpg 144340/144340 [==============================] - 0s 1us/step Downloading data from https://upload.wikimedia.org/wikipedia/commons/c/c5/Edvard_Munch%2C_1893%2C_The_Scream%2C_oil%2C_tempera_and_pastel_on_cardboard%2C_91_x_73_cm%2C_National_Gallery_of_Norway.jpg 11403121/11403121 [==============================] - 0s 0us/step Downloading data from https://upload.wikimedia.org/wikipedia/en/4/4c/Les_Demoiselles_d%27Avignon.jpg 2905099/2905099 [==============================] - 0s 0us/step Downloading data from https://upload.wikimedia.org/wikipedia/en/3/3c/Pablo_Picasso%2C_1911-12%2C_Violon_%28Violin%29%2C_oil_on_canvas%2C_Kr%C3%B6ller-M%C3%BCller_Museum%2C_Otterlo%2C_Netherlands.jpg 1234199/1234199 [==============================] - 0s 0us/step Downloading data from https://upload.wikimedia.org/wikipedia/en/7/7f/Pablo_Picasso%2C_1911%2C_Still_Life_with_a_Bottle_of_Rum%2C_oil_on_canvas%2C_61.3_x_50.5_cm%2C_Metropolitan_Museum_of_Art%2C_New_York.jpg 120288/120288 [==============================] - 0s 1us/step Downloading data from https://upload.wikimedia.org/wikipedia/commons/3/36/Large_bonfire.jpg 131604/131604 [==============================] - 0s 1us/step Downloading data from https://upload.wikimedia.org/wikipedia/commons/0/0d/Derkovits_Gyula_Woman_head_1922.jpg 32390/32390 [==============================] - 0s 1us/step Downloading data from https://upload.wikimedia.org/wikipedia/commons/8/8e/Untitled_%28Still_life%29_%281913%29_-_Amadeo_Souza-Cardoso_%281887-1918%29_%2817385824283%29.jpg 1914618/1914618 [==============================] - 0s 0us/step Downloading data from https://upload.wikimedia.org/wikipedia/commons/3/37/Derkovits_Gyula_Talig%C3%A1s_1920.jpg 40620/40620 [==============================] - 0s 1us/step Downloading data from https://upload.wikimedia.org/wikipedia/commons/7/7d/Amadeo_de_Souza-Cardoso%2C_1915_-_Landscape_with_black_figure.jpg 66306/66306 [==============================] - 0s 1us/step
Specify the main content image and the style you want to use.
content_name = 'sea_turtle' # @param ['sea_turtle', 'tuebingen', 'grace_hopper']
style_name = 'munch_scream' # @param ['kanagawa_great_wave', 'kandinsky_composition_7', 'hubble_pillars_of_creation', 'van_gogh_starry_night', 'turner_nantes', 'munch_scream', 'picasso_demoiselles_avignon', 'picasso_violin', 'picasso_bottle_of_rum', 'fire', 'derkovits_woman_head', 'amadeo_style_life', 'derkovtis_talig', 'amadeo_cardoso']
stylized_image = hub_module(tf.constant(content_images[content_name]),
tf.constant(style_images[style_name]))[0]
show_n([content_images[content_name], style_images[style_name], stylized_image],
titles=['Original content image', 'Style image', 'Stylized image'])
