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Transfer Gaya Cepat untuk Gaya Sewenang-wenang

Lihat di TensorFlow.org Jalankan di Google Colab Lihat sumber di GitHub Unduh buku catatan

Berdasarkan kode model di magenta dan publikasi:

Menjelajahi struktur jaringan stilisasi artistik saraf waktu nyata dan sewenang-wenang . Golnaz Ghiasi, Honglak Lee, Manjunath Kudlur, Vincent Dumoulin, Jonathon Shlens , Proceedings of the British Machine Vision Conference (BMVC), 2017.

Mempersiapkan

Mari kita mulai dengan mengimpor TF-2 dan semua dependensi yang relevan.

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.test.is_gpu_available())
TF Version:  2.2.0
TF-Hub version:  0.8.0
Eager mode enabled:  True
WARNING:tensorflow:From <ipython-input-2-1b40332be70f>:13: is_gpu_available (from tensorflow.python.framework.test_util) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.config.list_physical_devices('GPU')` instead.
GPU available:  True

# @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 = plt.imread(image_path).astype(np.float32)[np.newaxis, ...]
  if img.max() > 1.0:
    img = img / 255.
  if len(img.shape) == 3:
    img = tf.stack([img, img, img], axis=-1)
  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()

Mari kita dapatkan juga beberapa gambar untuk dimainkan.

# @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
65536/58102 [=================================] - 0s 2us/step
Downloading data from https://upload.wikimedia.org/wikipedia/commons/0/0a/The_Great_Wave_off_Kanagawa.jpg
2686976/2684586 [==============================] - 0s 0us/step

png

Impor modul TF-Hub

# Load TF-Hub module.

hub_handle = 'https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2'
hub_module = hub.load(hub_handle)

Tanda tangan modul hub ini untuk penataan gambar adalah:

outputs = hub_module(content_image, style_image)
stylized_image = outputs[0]

Di mana content_image , style_image , dan stylized_image diharapkan menjadi [batch_size, image_height, image_width, 3] 4-D dengan bentuk [batch_size, image_height, image_width, 3] .

Dalam contoh saat ini kami hanya menyediakan gambar tunggal dan oleh karena itu dimensi batch adalah 1, tetapi modul yang sama dapat digunakan untuk memproses lebih banyak gambar pada waktu yang sama.

Nilai input dan output gambar harus dalam kisaran [0, 1].

Bentuk konten dan gambar gaya tidak harus sama. Bentuk gambar keluaran sama dengan bentuk gambar isi.

Peragakan stilisasi gambar

# 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'])

png

Mari kita coba pada lebih banyak gambar

# @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
3178496/3170828 [==============================] - 0s 0us/step
Downloading data from https://upload.wikimedia.org/wikipedia/commons/0/00/Tuebingen_Neckarfront.jpg
409600/406531 [==============================] - 0s 1us/step
Downloading data from https://storage.googleapis.com/download.tensorflow.org/example_images/grace_hopper.jpg
65536/61306 [================================] - 0s 0us/step
Downloading data from https://upload.wikimedia.org/wikipedia/commons/b/b4/Vassily_Kandinsky%2C_1913_-_Composition_7.jpg
196608/195196 [==============================] - 0s 1us/step
Downloading data from https://upload.wikimedia.org/wikipedia/commons/6/68/Pillars_of_creation_2014_HST_WFC3-UVIS_full-res_denoised.jpg
46931968/46930988 [==============================] - 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
401408/396423 [==============================] - 0s 1us/step
Downloading data from https://upload.wikimedia.org/wikipedia/commons/b/b7/JMW_Turner_-_Nantes_from_the_Ile_Feydeau.jpg
147456/144340 [==============================] - 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
11403264/11403121 [==============================] - 1s 0us/step
Downloading data from https://upload.wikimedia.org/wikipedia/en/4/4c/Les_Demoiselles_d%27Avignon.jpg
2908160/2905099 [==============================] - 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
1236992/1234199 [==============================] - 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
122880/120288 [==============================] - 0s 2us/step
Downloading data from https://upload.wikimedia.org/wikipedia/commons/3/36/Large_bonfire.jpg
139264/131604 [===============================] - 0s 1us/step
Downloading data from https://upload.wikimedia.org/wikipedia/commons/0/0d/Derkovits_Gyula_Woman_head_1922.jpg
32768/32390 [==============================] - 0s 2us/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
1916928/1914618 [==============================] - 0s 0us/step
Downloading data from https://upload.wikimedia.org/wikipedia/commons/3/37/Derkovits_Gyula_Talig%C3%A1s_1920.jpg
40960/40620 [==============================] - 0s 2us/step
Downloading data from https://upload.wikimedia.org/wikipedia/commons/7/7d/Amadeo_de_Souza-Cardoso%2C_1915_-_Landscape_with_black_figure.jpg
73728/66306 [=================================] - 0s 2us/step



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'])

png