mirror of
https://github.com/iperov/DeepFaceLab.git
synced 2025-07-06 04:52:13 -07:00
manual extractor: increased FPS,
sort by final : now you can specify target number of images, converter: fix seamless mask and exception, huge refactoring
This commit is contained in:
iperov
parent
7db469a1da
commit
438213e97c
30 changed files with 1834 additions and 1718 deletions
104
main.py
104
main.py
|
|
@ -1,5 +1,6 @@
|
|||
import os
|
||||
import sys
|
||||
import time
|
||||
import argparse
|
||||
from utils import Path_utils
|
||||
from utils import os_utils
|
||||
|
|
@ -12,35 +13,26 @@ class fixPathAction(argparse.Action):
|
|||
def __call__(self, parser, namespace, values, option_string=None):
|
||||
setattr(namespace, self.dest, os.path.abspath(os.path.expanduser(values)))
|
||||
|
||||
def str2bool(v):
|
||||
if v.lower() in ('yes', 'true', 't', 'y', '1'):
|
||||
return True
|
||||
elif v.lower() in ('no', 'false', 'f', 'n', '0'):
|
||||
return False
|
||||
else:
|
||||
raise argparse.ArgumentTypeError('Boolean value expected.')
|
||||
|
||||
if __name__ == "__main__":
|
||||
os_utils.set_process_lowest_prio()
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument('--tf-suppress-std', action="store_true", dest="tf_suppress_std", default=False, help="Suppress tensorflow initialization info. May not works on some python builds such as anaconda python 3.6.4. If you can fix it, you are welcome.")
|
||||
|
||||
|
||||
subparsers = parser.add_subparsers()
|
||||
|
||||
def process_extract(arguments):
|
||||
from mainscripts import Extractor
|
||||
Extractor.main (
|
||||
input_dir=arguments.input_dir,
|
||||
output_dir=arguments.output_dir,
|
||||
debug=arguments.debug,
|
||||
face_type=arguments.face_type,
|
||||
detector=arguments.detector,
|
||||
multi_gpu=arguments.multi_gpu,
|
||||
cpu_only=arguments.cpu_only,
|
||||
manual_fix=arguments.manual_fix,
|
||||
manual_output_debug_fix=arguments.manual_output_debug_fix,
|
||||
manual_window_size=arguments.manual_window_size
|
||||
)
|
||||
from mainscripts import Extractor
|
||||
Extractor.main( arguments.input_dir,
|
||||
arguments.output_dir,
|
||||
arguments.debug,
|
||||
arguments.detector,
|
||||
arguments.manual_fix,
|
||||
arguments.manual_output_debug_fix,
|
||||
arguments.manual_window_size,
|
||||
face_type=arguments.face_type,
|
||||
device_args={'cpu_only' : arguments.cpu_only,
|
||||
'multi_gpu' : arguments.multi_gpu,
|
||||
}
|
||||
)
|
||||
|
||||
extract_parser = subparsers.add_parser( "extract", help="Extract the faces from a pictures.")
|
||||
extract_parser.add_argument('--input-dir', required=True, action=fixPathAction, dest="input_dir", help="Input directory. A directory containing the files you wish to process.")
|
||||
|
|
@ -79,24 +71,26 @@ if __name__ == "__main__":
|
|||
util_parser.add_argument('--add-landmarks-debug-images', action="store_true", dest="add_landmarks_debug_images", default=False, help="Add landmarks debug image for aligned faces.")
|
||||
util_parser.set_defaults (func=process_util)
|
||||
|
||||
def process_train(arguments):
|
||||
from mainscripts import Trainer
|
||||
Trainer.main (
|
||||
training_data_src_dir=arguments.training_data_src_dir,
|
||||
training_data_dst_dir=arguments.training_data_dst_dir,
|
||||
model_path=arguments.model_dir,
|
||||
model_name=arguments.model_name,
|
||||
debug = arguments.debug,
|
||||
#**options
|
||||
force_gpu_idx = arguments.force_gpu_idx,
|
||||
cpu_only = arguments.cpu_only
|
||||
)
|
||||
|
||||
def process_train(arguments):
|
||||
args = {'training_data_src_dir' : arguments.training_data_src_dir,
|
||||
'training_data_dst_dir' : arguments.training_data_dst_dir,
|
||||
'model_path' : arguments.model_dir,
|
||||
'model_name' : arguments.model_name,
|
||||
'no_preview' : arguments.no_preview,
|
||||
'debug' : arguments.debug,
|
||||
}
|
||||
device_args = {'cpu_only' : arguments.cpu_only,
|
||||
'force_gpu_idx' : arguments.force_gpu_idx,
|
||||
}
|
||||
from mainscripts import Trainer
|
||||
Trainer.main(args, device_args)
|
||||
|
||||
train_parser = subparsers.add_parser( "train", help="Trainer")
|
||||
train_parser.add_argument('--training-data-src-dir', required=True, action=fixPathAction, dest="training_data_src_dir", help="Dir of src-set.")
|
||||
train_parser.add_argument('--training-data-dst-dir', required=True, action=fixPathAction, dest="training_data_dst_dir", help="Dir of dst-set.")
|
||||
train_parser.add_argument('--model-dir', required=True, action=fixPathAction, dest="model_dir", help="Model dir.")
|
||||
train_parser.add_argument('--model', required=True, dest="model_name", choices=Path_utils.get_all_dir_names_startswith ( Path(__file__).parent / 'models' , 'Model_'), help="Type of model")
|
||||
train_parser.add_argument('--no-preview', action="store_true", dest="no_preview", default=False, help="Disable preview window.")
|
||||
train_parser.add_argument('--debug', action="store_true", dest="debug", default=False, help="Debug samples.")
|
||||
train_parser.add_argument('--cpu-only', action="store_true", dest="cpu_only", default=False, help="Train on CPU.")
|
||||
train_parser.add_argument('--force-gpu-idx', type=int, dest="force_gpu_idx", default=-1, help="Force to choose this GPU idx.")
|
||||
|
|
@ -104,17 +98,18 @@ if __name__ == "__main__":
|
|||
train_parser.set_defaults (func=process_train)
|
||||
|
||||
def process_convert(arguments):
|
||||
args = {'input_dir' : arguments.input_dir,
|
||||
'output_dir' : arguments.output_dir,
|
||||
'aligned_dir' : arguments.aligned_dir,
|
||||
'model_dir' : arguments.model_dir,
|
||||
'model_name' : arguments.model_name,
|
||||
'debug' : arguments.debug,
|
||||
}
|
||||
device_args = {'cpu_only' : arguments.cpu_only,
|
||||
'force_gpu_idx' : arguments.force_gpu_idx,
|
||||
}
|
||||
from mainscripts import Converter
|
||||
Converter.main (
|
||||
input_dir=arguments.input_dir,
|
||||
output_dir=arguments.output_dir,
|
||||
aligned_dir=arguments.aligned_dir,
|
||||
model_dir=arguments.model_dir,
|
||||
model_name=arguments.model_name,
|
||||
debug = arguments.debug,
|
||||
force_gpu_idx = arguments.force_gpu_idx,
|
||||
cpu_only = arguments.cpu_only
|
||||
)
|
||||
Converter.main (args, device_args)
|
||||
|
||||
convert_parser = subparsers.add_parser( "convert", help="Converter")
|
||||
convert_parser.add_argument('--input-dir', required=True, action=fixPathAction, dest="input_dir", help="Input directory. A directory containing the files you wish to process.")
|
||||
|
|
@ -134,14 +129,27 @@ if __name__ == "__main__":
|
|||
parser.set_defaults(func=bad_args)
|
||||
|
||||
arguments = parser.parse_args()
|
||||
if arguments.tf_suppress_std:
|
||||
os.environ['TF_SUPPRESS_STD'] = '1'
|
||||
|
||||
#os.environ['force_plaidML'] = '1'
|
||||
|
||||
arguments.func(arguments)
|
||||
|
||||
print ("Done.")
|
||||
|
||||
"""
|
||||
Suppressing error with keras 2.2.4+ on python exit:
|
||||
|
||||
Exception ignored in: <bound method BaseSession._Callable.__del__ of <tensorflow.python.client.session.BaseSession._Callable object at 0x000000001BDEA9B0>>
|
||||
Traceback (most recent call last):
|
||||
File "D:\DeepFaceLab\_internal\bin\lib\site-packages\tensorflow\python\client\session.py", line 1413, in __del__
|
||||
AttributeError: 'NoneType' object has no attribute 'raise_exception_on_not_ok_status'
|
||||
|
||||
reproduce: https://github.com/keras-team/keras/issues/11751 ( still no solution )
|
||||
"""
|
||||
outnull_file = open(os.devnull, 'w')
|
||||
os.dup2 ( outnull_file.fileno(), sys.stderr.fileno() )
|
||||
sys.stderr = outnull_file
|
||||
|
||||
|
||||
'''
|
||||
import code
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue