main.py

# MIT License

# Copyright (c) 2020 Patrik Persson and Linn Öström

# 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.


import yaml
import argparse
from Trainer.Manager import Manager
import tensorflow as tf


if __name__ == '__main__':

    gpus = tf.config.experimental.list_physical_devices('GPU')

    if gpus:
        try:
            for gpu in gpus:
                tf.config.experimental.set_memory_growth(gpu, True)
        except RuntimeError as e:
            print(e)

    parser = argparse.ArgumentParser()

    parser.add_argument('config', type=str)
    parser.add_argument('--dataset', '--d', default="",
                        type=str, required=False)

    args = parser.parse_args()

    with open(args.config, 'r') as stream:
        try:
            config = yaml.safe_load(stream)

            if args.dataset:

                config["sfm_dataset"]["datasets"] = [args.dataset]

            Manager(config).run()

        except yaml.YAMLError as exc:
            print(exc)