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optimized face sample generator, CPU load is significantly reduced

Browse source 
SAEHD:

added new option
GAN power 0.0 .. 10.0
	Train the network in Generative Adversarial manner.
	Forces the neural network to learn small details of the face.
	You can enable/disable this option at any time,
	but better to enable it when the network is trained enough.
	Typical value is 1.0
	GAN power with pretrain mode will not work.

Example of enabling GAN on 81k iters +5k iters
https://i.imgur.com/OdXHLhU.jpg
https://i.imgur.com/CYAJmJx.jpg

dfhd: default Decoder dimensions are now 48
the preview for 256 res is now correctly displayed

fixed model naming/renaming/removing

Improvements for those involved in post-processing in AfterEffects:

Codec is reverted back to x264 in order to properly use in AfterEffects and video players.

Merger now always outputs the mask to workspace\data_dst\merged_mask

removed raw modes except raw-rgb
raw-rgb mode now outputs selected face mask_mode (before square mask)

'export alpha mask' button is replaced by 'show alpha mask'.
You can view the alpha mask without recompute the frames.

8) 'merged *.bat' now also output 'result_mask.' video file.
8) 'merged lossless' now uses x264 lossless codec (before PNG codec)
result_mask video file is always lossless.

Thus you can use result_mask video file as mask layer in the AfterEffects.
This commit is contained in:
Colombo 2020-01-28 12:24:45 +04:00
parent 80f285067a
commit 7386a9d6fd
28 changed files with 455 additions and 363 deletions
Download patch file Download diff file Expand all files Collapse all files

39
main.py
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@ -201,23 +201,23 @@ if __name__ == "__main__":
def process_merge(arguments):
osex.set_process_lowest_prio()
kwargs = {'model_class_name' : arguments.model_name,
'saved_models_path' : Path(arguments.model_dir),
'training_data_src_path' : Path(arguments.training_data_src_dir) if arguments.training_data_src_dir is not None else None,
'force_model_name' : arguments.force_model_name,
'input_path' : Path(arguments.input_dir),
'output_path' : Path(arguments.output_dir),
'aligned_path' : Path(arguments.aligned_dir) if arguments.aligned_dir is not None else None,
'cpu_only' : arguments.cpu_only,
'force_gpu_idxs' : arguments.force_gpu_idxs,
}
from mainscripts import Merger
Merger.main (**kwargs)
Merger.main ( model_class_name = arguments.model_name,
saved_models_path = Path(arguments.model_dir),
training_data_src_path = Path(arguments.training_data_src_dir) if arguments.training_data_src_dir is not None else None,
force_model_name = arguments.force_model_name,
input_path = Path(arguments.input_dir),
output_path = Path(arguments.output_dir),
output_mask_path = Path(arguments.output_mask_dir),
aligned_path = Path(arguments.aligned_dir) if arguments.aligned_dir is not None else None,
force_gpu_idxs = arguments.force_gpu_idxs,
cpu_only = arguments.cpu_only)
p = subparsers.add_parser( "merge", help="Merger")
p.add_argument('--training-data-src-dir', action=fixPathAction, dest="training_data_src_dir", default=None, help="(optional, may be required by some models) Dir of extracted SRC faceset.")
p.add_argument('--input-dir', required=True, action=fixPathAction, dest="input_dir", help="Input directory. A directory containing the files you wish to process.")
p.add_argument('--output-dir', required=True, action=fixPathAction, dest="output_dir", help="Output directory. This is where the merged files will be stored.")
p.add_argument('--output-mask-dir', required=True, action=fixPathAction, dest="output_mask_dir", help="Output mask directory. This is where the mask files will be stored.")
p.add_argument('--aligned-dir', action=fixPathAction, dest="aligned_dir", default=None, help="Aligned directory. This is where the extracted of dst faces stored.")
p.add_argument('--model-dir', required=True, action=fixPathAction, dest="model_dir", help="Model dir.")
p.add_argument('--model', required=True, dest="model_name", choices=pathex.get_all_dir_names_startswith ( Path(__file__).parent / 'models' , 'Model_'), help="Model class name.")
@ -268,13 +268,14 @@ if __name__ == "__main__":
def process_videoed_video_from_sequence(arguments):
osex.set_process_lowest_prio()
from mainscripts import VideoEd
VideoEd.video_from_sequence (arguments.input_dir,
arguments.output_file,
arguments.reference_file,
arguments.ext,
arguments.fps,
arguments.bitrate,
arguments.lossless)
VideoEd.video_from_sequence (input_dir = arguments.input_dir,
output_file = arguments.output_file,
reference_file = arguments.reference_file,
ext = arguments.ext,
fps = arguments.fps,
bitrate = arguments.bitrate,
include_audio = arguments.include_audio,
lossless = arguments.lossless)
p = videoed_parser.add_parser( "video-from-sequence", help="Make video from image sequence.")
p.add_argument('--input-dir', required=True, action=fixPathAction, dest="input_dir", help="Input file to be processed. Specify .*-extension to find first file.")
@ -283,7 +284,9 @@ if __name__ == "__main__":
p.add_argument('--ext', dest="ext", default='png', help="Image format (extension) of input files.")
p.add_argument('--fps', type=int, dest="fps", default=None, help="FPS of output file. Overwritten by reference-file.")
p.add_argument('--bitrate', type=int, dest="bitrate", default=None, help="Bitrate of output file in Megabits.")
p.add_argument('--include-audio', action="store_true", dest="include_audio", default=False, help="Include audio from reference file.")
p.add_argument('--lossless', action="store_true", dest="lossless", default=False, help="PNG codec.")
p.set_defaults(func=process_videoed_video_from_sequence)
def process_labelingtool_edit_mask(arguments):