DeepFaceLab/samplelib/PackedFaceset.py
Colombo 50f892d57d all models: removed options 'src_scale_mod', and 'sort samples by yaw as target'
If you want, you can manually remove unnecessary angles from src faceset after sort by yaw.

Optimized sample generators (CPU workers). Now they consume less amount of RAM and work faster.

added
4.2.other) data_src/dst util faceset pack.bat
	Packs /aligned/ samples into one /aligned/samples.pak file.
	After that, all faces will be deleted.

4.2.other) data_src/dst util faceset unpack.bat
	unpacks faces from /aligned/samples.pak to /aligned/ dir.
	After that, samples.pak will be deleted.

Packed faceset load and work faster.
2019-12-21 23:16:55 +04:00

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Python

import pickle
import struct
from pathlib import Path
from interact import interact as io
from utils import Path_utils
import samplelib.SampleHost
packed_faceset_filename = 'samples.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_bool("Press enter to continue and overwrite.", False)
of = open(samples_dat_path, "wb")
image_paths = Path_utils.get_image_paths(samples_path)
samples = samplelib.SampleHost.load_face_samples(image_paths)
for sample in samples:
sample.filename = str(Path(sample.filename).relative_to(samples_path))
samples_len = len(samples)
samples_bytes = pickle.dumps(samples, 4)
of.write ( struct.pack ("Q", PackedFaceset.VERSION ) )
of.write ( struct.pack ("Q", len(samples_bytes) ) )
of.write ( samples_bytes )
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:
with open( samples_path / sample.filename, "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.filename}")
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"):
Path(filename).unlink()
@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"):
with open(samples_path / sample.filename, "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 = pickle.loads ( f.read(sizeof_samples_bytes) )
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