def train(self, input_a_dir, input_b_dir, model_dir, gan = False):
model_type = "Original"
if gan:
model_type = "GAN"
train = TrainingProcessor(
self._subparser, "train", "This command trains the model for the two faces A and B.")
args_str = "train --input-A {} --input-B {} --model-dir {} --trainer {} --batch-size {} --write-image -p"
args_str = args_str.format(input_a_dir, input_b_dir, model_dir, model_type, 512)
self._run_script(args_str)
import sys
if sys.version_info[0] < 3:
raise Exception("This program requires at least python3.2")
if sys.version_info[0] == 3 and sys.version_info[1] < 2:
raise Exception("This program requires at least python3.2")
from lib.utils import FullHelpArgumentParser
from scripts.extract import ExtractTrainingData
from scripts.train import TrainingProcessor
from scripts.convert import ConvertImage
from tensorflow.compat.v1 import ConfigProto
from tensorflow.compat.v1 import InteractiveSession
config = ConfigProto()
config.gpu_options.allow_growth = True
session = InteractiveSession(config=config)
if __name__ == "__main__":
parser = FullHelpArgumentParser()
subparser = parser.add_subparsers()
extract = ExtractTrainingData(
subparser, "extract", "Extract the faces from a pictures.")
train = TrainingProcessor(
subparser, "train", "This command trains the model for the two faces A and B.")
convert = ConvertImage(
subparser, "convert", "Convert a source image to a new one with the face swapped.")
arguments = parser.parse_args()
arguments.func(arguments)