main.py

# MIT License
#
# Copyright (c) 2019 Drew Szurko
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals

from absl import app
from absl import flags
from tensorflow import keras

import models
from utils import load_img

keras.backend.clear_session()

flags.DEFINE_string('content_path', 'chomper3.jpg', 'Path to content image.')
flags.DEFINE_string('style_path', 'art18.jpg', 'Path to style image.')
flags.DEFINE_string('output_dir', '.', 'Output directory.')
flags.DEFINE_integer('epochs', 20, 'Epochs to train.')
flags.DEFINE_integer('steps_per_epoch', 500, 'Steps per epoch.')
flags.DEFINE_float('tv_weight', 1e8, 'Total variation weight.')
flags.DEFINE_float('content_weight', 10000, 'Content weight.')
flags.DEFINE_float('style_weight', 0.10, 'Style weight.')
flags.DEFINE_float('learning_rate', 0.02, 'Learning rate.')
flags.DEFINE_float('beta_1', 0.99, 'Beta 1.')
flags.DEFINE_float('beta_2', 0.999, 'Beta 2.')
flags.DEFINE_float('epsilon', 0.10, 'Epsilon.')
flags.DEFINE_float('max_dim', 512, 'Max dimension to crop I/O image.')
flags.mark_flags_as_required(['content_path', 'style_path'])
FLAGS = flags.FLAGS


def main(argv):
    del argv

    content_img = load_img(FLAGS.content_path)
    style_img = load_img(FLAGS.style_path)

    mdl = models.StyleContent(content_img, style_img)
    mdl.train()


if __name__ == '__main__':
    app.run(main)