mirror of
https://github.com/iperov/DeepFaceLab.git
synced 2025-03-12 20:42:45 -07:00
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.
151 lines
5.1 KiB
Python
151 lines
5.1 KiB
Python
import pickle
|
|
import shutil
|
|
import struct
|
|
from pathlib import Path
|
|
|
|
import samplelib.SampleLoader
|
|
from core.interact import interact as io
|
|
from samplelib import Sample
|
|
from core import pathex
|
|
|
|
packed_faceset_filename = 'faceset.pak'
|
|
|
|
class PackedFaceset():
|
|
VERSION = 1
|
|
|
|
@staticmethod
|
|
def pack(samples_path):
|
|
samples_dat_path = samples_path / packed_faceset_filename
|
|
|
|
if samples_dat_path.exists():
|
|
io.log_info(f"{samples_dat_path} : file already exists !")
|
|
io.input("Press enter to continue and overwrite.")
|
|
|
|
as_person_faceset = False
|
|
dir_names = pathex.get_all_dir_names(samples_path)
|
|
if len(dir_names) != 0:
|
|
as_person_faceset = io.input_bool(f"{len(dir_names)} subdirectories found, process as person faceset?", True)
|
|
|
|
if as_person_faceset:
|
|
image_paths = []
|
|
|
|
for dir_name in dir_names:
|
|
image_paths += pathex.get_image_paths(samples_path / dir_name)
|
|
else:
|
|
image_paths = pathex.get_image_paths(samples_path)
|
|
|
|
samples = samplelib.SampleLoader.load_face_samples(image_paths)
|
|
samples_len = len(samples)
|
|
|
|
samples_configs = []
|
|
for sample in io.progress_bar_generator (samples, "Processing"):
|
|
sample_filepath = Path(sample.filename)
|
|
sample.filename = sample_filepath.name
|
|
|
|
if as_person_faceset:
|
|
sample.person_name = sample_filepath.parent.name
|
|
samples_configs.append ( sample.get_config() )
|
|
samples_bytes = pickle.dumps(samples_configs, 4)
|
|
|
|
of = open(samples_dat_path, "wb")
|
|
of.write ( struct.pack ("Q", PackedFaceset.VERSION ) )
|
|
of.write ( struct.pack ("Q", len(samples_bytes) ) )
|
|
of.write ( samples_bytes )
|
|
|
|
del samples_bytes #just free mem
|
|
del samples_configs
|
|
|
|
sample_data_table_offset = of.tell()
|
|
of.write ( bytes( 8*(samples_len+1) ) ) #sample data offset table
|
|
|
|
data_start_offset = of.tell()
|
|
offsets = []
|
|
|
|
for sample in io.progress_bar_generator(samples, "Packing"):
|
|
try:
|
|
if sample.person_name is not None:
|
|
sample_path = samples_path / sample.person_name / sample.filename
|
|
else:
|
|
sample_path = samples_path / sample.filename
|
|
|
|
|
|
with open(sample_path, "rb") as f:
|
|
b = f.read()
|
|
|
|
offsets.append ( of.tell() - data_start_offset )
|
|
of.write(b)
|
|
except:
|
|
raise Exception(f"error while processing sample {sample_path}")
|
|
|
|
offsets.append ( of.tell() )
|
|
|
|
of.seek(sample_data_table_offset, 0)
|
|
for offset in offsets:
|
|
of.write ( struct.pack("Q", offset) )
|
|
of.seek(0,2)
|
|
of.close()
|
|
|
|
for filename in io.progress_bar_generator(image_paths, "Deleting files"):
|
|
Path(filename).unlink()
|
|
|
|
if as_person_faceset:
|
|
for dir_name in io.progress_bar_generator(dir_names, "Deleting dirs"):
|
|
dir_path = samples_path / dir_name
|
|
try:
|
|
shutil.rmtree(dir_path)
|
|
except:
|
|
io.log_info (f"unable to remove: {dir_path} ")
|
|
|
|
@staticmethod
|
|
def unpack(samples_path):
|
|
samples_dat_path = samples_path / packed_faceset_filename
|
|
if not samples_dat_path.exists():
|
|
io.log_info(f"{samples_dat_path} : file not found.")
|
|
return
|
|
|
|
samples = PackedFaceset.load(samples_path)
|
|
|
|
for sample in io.progress_bar_generator(samples, "Unpacking"):
|
|
person_name = sample.person_name
|
|
if person_name is not None:
|
|
person_path = samples_path / person_name
|
|
person_path.mkdir(parents=True, exist_ok=True)
|
|
|
|
target_filepath = person_path / sample.filename
|
|
else:
|
|
target_filepath = samples_path / sample.filename
|
|
|
|
with open(target_filepath, "wb") as f:
|
|
f.write( sample.read_raw_file() )
|
|
|
|
samples_dat_path.unlink()
|
|
|
|
@staticmethod
|
|
def load(samples_path):
|
|
samples_dat_path = samples_path / packed_faceset_filename
|
|
if not samples_dat_path.exists():
|
|
return None
|
|
|
|
f = open(samples_dat_path, "rb")
|
|
version, = struct.unpack("Q", f.read(8) )
|
|
if version != PackedFaceset.VERSION:
|
|
raise NotImplementedError
|
|
|
|
sizeof_samples_bytes, = struct.unpack("Q", f.read(8) )
|
|
|
|
samples_configs = pickle.loads ( f.read(sizeof_samples_bytes) )
|
|
samples = []
|
|
for sample_config in samples_configs:
|
|
sample_config = pickle.loads(pickle.dumps (sample_config))
|
|
samples.append ( Sample (**sample_config) )
|
|
|
|
offsets = [ struct.unpack("Q", f.read(8) )[0] for _ in range(len(samples)+1) ]
|
|
data_start_offset = f.tell()
|
|
f.close()
|
|
|
|
for i, sample in enumerate(samples):
|
|
start_offset, end_offset = offsets[i], offsets[i+1]
|
|
sample.set_filename_offset_size( str(samples_dat_path), data_start_offset+start_offset, end_offset-start_offset )
|
|
|
|
return samples
|