"""

If you use this code, please cite one of the SynthSeg papers:

https://github.com/BBillot/SynthSeg/blob/master/bibtex.bib

Copyright 2020 Benjamin Billot

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in

compliance with the License. You may obtain a copy of the License at

https://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is

distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or

implied. See the License for the specific language governing permissions and limitations under the

License.

"""

from argparse import ArgumentParser

from SynthSeg.training import training

from ext.lab2im.utils import infer

parser = ArgumentParser()

# ------------------------------------------------- General parameters -------------------------------------------------

# Positional arguments

parser.add_argument("labels_dir", type=str)

parser.add_argument("model_dir", type=str)

# ---------------------------------------------- Generation parameters ----------------------------------------------

# label maps parameters

parser.add_argument("--generation_labels", type=str, dest="generation_labels", default=None)

parser.add_argument("--neutral_labels", type=int, dest="n_neutral_labels", default=None)

parser.add_argument("--segmentation_labels", type=str, dest="segmentation_labels", default=None)

parser.add_argument("--subjects_prob", type=str, dest="subjects_prob", default=None)

# output-related parameters

parser.add_argument("--batch_size", type=int, dest="batchsize", default=1)

parser.add_argument("--channels", type=int, dest="n_channels", default=1)

parser.add_argument("--target_res", type=float, dest="target_res", default=None)

parser.add_argument("--output_shape", type=int, dest="output_shape", default=None)

# GMM-sampling parameters

parser.add_argument("--generation_classes", type=str, dest="generation_classes", default=None)

parser.add_argument("--prior_type", type=str, dest="prior_distributions", default='uniform')

parser.add_argument("--prior_means", type=str, dest="prior_means", default=None)

parser.add_argument("--prior_stds", type=str, dest="prior_stds", default=None)

parser.add_argument("--specific_stats", action='store_true', dest="use_specific_stats_for_channel")

parser.add_argument("--mix_prior_and_random", action='store_true', dest="mix_prior_and_random")

# spatial deformation parameters

parser.add_argument("--no_flipping", action='store_false', dest="flipping")

parser.add_argument("--scaling", dest="scaling_bounds", type=infer, default=0.2)

parser.add_argument("--rotation", dest="rotation_bounds", type=infer, default=15)

parser.add_argument("--shearing", dest="shearing_bounds", type=infer, default=.012)

parser.add_argument("--translation", dest="translation_bounds", type=infer, default=False)

parser.add_argument("--nonlin_std", type=float, dest="nonlin_std", default=4.)

parser.add_argument("--nonlin_scale", type=float, dest="nonlin_scale", default=.04)

# blurring/resampling parameters

parser.add_argument("--randomise_res", action='store_true', dest="randomise_res")

parser.add_argument("--max_res_iso", type=float, dest="max_res_iso", default=4.)

parser.add_argument("--max_res_aniso", type=float, dest="max_res_aniso", default=8.)

parser.add_argument("--data_res", dest="data_res", type=infer, default=None)

parser.add_argument("--thickness", dest="thickness", type=infer, default=None)

# bias field parameters

parser.add_argument("--bias_std", type=float, dest="bias_field_std", default=.7)

parser.add_argument("--bias_scale", type=float, dest="bias_scale", default=.025)

parser.add_argument("--gradients", action='store_true', dest="return_gradients")

# -------------------------------------------- UNet architecture parameters --------------------------------------------

parser.add_argument("--n_levels", type=int, dest="n_levels", default=5)

parser.add_argument("--conv_per_level", type=int, dest="nb_conv_per_level", default=2)

parser.add_argument("--conv_size", type=int, dest="conv_size", default=3)

parser.add_argument("--unet_feat", type=int, dest="unet_feat_count", default=24)

parser.add_argument("--feat_mult", type=int, dest="feat_multiplier", default=2)

parser.add_argument("--activation", type=str, dest="activation", default='elu')

# ------------------------------------------------- Training parameters ------------------------------------------------

parser.add_argument("--lr", type=float, dest="lr", default=1e-4)

parser.add_argument("--wl2_epochs", type=int, dest="wl2_epochs", default=1)

parser.add_argument("--dice_epochs", type=int, dest="dice_epochs", default=50)

parser.add_argument("--steps_per_epoch", type=int, dest="steps_per_epoch", default=10000)

parser.add_argument("--checkpoint", type=str, dest="checkpoint", default=None)

args = parser.parse_args()

training(**vars(args))