mirror of
https://github.com/iperov/DeepFaceLab.git
synced 2025-07-06 04:52:13 -07:00
fe58459f36
Synthesize new faces from existing ones by relighting them using DeepPortraitRelighter network. With the relighted faces neural network will better reproduce face shadows. Therefore you can synthsize shadowed faces from fully lit faceset. https://i.imgur.com/wxcmQoi.jpg as a result, better fakes on dark faces: https://i.imgur.com/5xXIbz5.jpg in OpenCL build Relighter runs on CPU, install pytorch directly via pip install, look at requirements
430 lines
15 KiB
Python
430 lines
15 KiB
Python
import pickle
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import string
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import struct
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import zlib
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import cv2
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import numpy as np
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from facelib import FaceType
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from imagelib import IEPolys
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PNG_HEADER = b"\x89PNG\r\n\x1a\n"
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class Chunk(object):
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def __init__(self, name=None, data=None):
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self.length = 0
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self.crc = 0
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self.name = name if name else "noNe"
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self.data = data if data else b""
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@classmethod
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def load(cls, data):
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"""Load a chunk including header and footer"""
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inst = cls()
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if len(data) < 12:
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msg = "Chunk-data too small"
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raise ValueError(msg)
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# chunk header & data
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(inst.length, raw_name) = struct.unpack("!I4s", data[0:8])
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inst.data = data[8:-4]
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inst.verify_length()
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inst.name = raw_name.decode("ascii")
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inst.verify_name()
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# chunk crc
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inst.crc = struct.unpack("!I", data[8+inst.length:8+inst.length+4])[0]
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inst.verify_crc()
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return inst
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def dump(self, auto_crc=True, auto_length=True):
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"""Return the chunk including header and footer"""
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if auto_length: self.update_length()
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if auto_crc: self.update_crc()
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self.verify_name()
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return struct.pack("!I", self.length) + self.get_raw_name() + self.data + struct.pack("!I", self.crc)
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def verify_length(self):
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if len(self.data) != self.length:
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msg = "Data length ({}) does not match length in chunk header ({})".format(len(self.data), self.length)
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raise ValueError(msg)
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return True
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def verify_name(self):
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for c in self.name:
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if c not in string.ascii_letters:
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msg = "Invalid character in chunk name: {}".format(repr(self.name))
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raise ValueError(msg)
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return True
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def verify_crc(self):
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calculated_crc = self.get_crc()
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if self.crc != calculated_crc:
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msg = "CRC mismatch: {:08X} (header), {:08X} (calculated)".format(self.crc, calculated_crc)
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raise ValueError(msg)
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return True
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def update_length(self):
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self.length = len(self.data)
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def update_crc(self):
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self.crc = self.get_crc()
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def get_crc(self):
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return zlib.crc32(self.get_raw_name() + self.data)
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def get_raw_name(self):
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return self.name if isinstance(self.name, bytes) else self.name.encode("ascii")
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# name helper methods
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def ancillary(self, set=None):
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"""Set and get ancillary=True/critical=False bit"""
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if set is True:
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self.name[0] = self.name[0].lower()
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elif set is False:
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self.name[0] = self.name[0].upper()
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return self.name[0].islower()
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def private(self, set=None):
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"""Set and get private=True/public=False bit"""
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if set is True:
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self.name[1] = self.name[1].lower()
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elif set is False:
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self.name[1] = self.name[1].upper()
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return self.name[1].islower()
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def reserved(self, set=None):
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"""Set and get reserved_valid=True/invalid=False bit"""
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if set is True:
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self.name[2] = self.name[2].upper()
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elif set is False:
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self.name[2] = self.name[2].lower()
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return self.name[2].isupper()
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def safe_to_copy(self, set=None):
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"""Set and get save_to_copy=True/unsafe=False bit"""
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if set is True:
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self.name[3] = self.name[3].lower()
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elif set is False:
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self.name[3] = self.name[3].upper()
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return self.name[3].islower()
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def __str__(self):
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return "<Chunk '{name}' length={length} crc={crc:08X}>".format(**self.__dict__)
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class IHDR(Chunk):
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"""IHDR Chunk
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width, height, bit_depth, color_type, compression_method,
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filter_method, interlace_method contain the data extracted
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from the chunk. Modify those and use and build() to recreate
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the chunk. Valid values for bit_depth depend on the color_type
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and can be looked up in color_types or in the PNG specification
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See:
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http://www.libpng.org/pub/png/spec/1.2/PNG-Chunks.html#C.IHDR
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"""
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# color types with name & allowed bit depths
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COLOR_TYPE_GRAY = 0
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COLOR_TYPE_RGB = 2
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COLOR_TYPE_PLTE = 3
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COLOR_TYPE_GRAYA = 4
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COLOR_TYPE_RGBA = 6
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color_types = {
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COLOR_TYPE_GRAY: ("Grayscale", (1,2,4,8,16)),
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COLOR_TYPE_RGB: ("RGB", (8,16)),
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COLOR_TYPE_PLTE: ("Palette", (1,2,4,8)),
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COLOR_TYPE_GRAYA: ("Greyscale+Alpha", (8,16)),
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COLOR_TYPE_RGBA: ("RGBA", (8,16)),
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}
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def __init__(self, width=0, height=0, bit_depth=8, color_type=2, \
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compression_method=0, filter_method=0, interlace_method=0):
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self.width = width
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self.height = height
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self.bit_depth = bit_depth
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self.color_type = color_type
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self.compression_method = compression_method
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self.filter_method = filter_method
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self.interlace_method = interlace_method
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super().__init__("IHDR")
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@classmethod
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def load(cls, data):
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inst = super().load(data)
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fields = struct.unpack("!IIBBBBB", inst.data)
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inst.width = fields[0]
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inst.height = fields[1]
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inst.bit_depth = fields[2] # per channel
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inst.color_type = fields[3] # see specs
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inst.compression_method = fields[4] # always 0(=deflate/inflate)
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inst.filter_method = fields[5] # always 0(=adaptive filtering with 5 methods)
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inst.interlace_method = fields[6] # 0(=no interlace) or 1(=Adam7 interlace)
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return inst
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def dump(self):
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self.data = struct.pack("!IIBBBBB", \
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self.width, self.height, self.bit_depth, self.color_type, \
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self.compression_method, self.filter_method, self.interlace_method)
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return super().dump()
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def __str__(self):
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return "<Chunk:IHDR geometry={width}x{height} bit_depth={bit_depth} color_type={}>" \
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.format(self.color_types[self.color_type][0], **self.__dict__)
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class IEND(Chunk):
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def __init__(self):
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super().__init__("IEND")
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def dump(self):
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if len(self.data) != 0:
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msg = "IEND has data which is not allowed"
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raise ValueError(msg)
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if self.length != 0:
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msg = "IEND data lenght is not 0 which is not allowed"
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raise ValueError(msg)
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return super().dump()
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def __str__(self):
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return "<Chunk:IEND>".format(**self.__dict__)
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class DFLChunk(Chunk):
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def __init__(self, dict_data=None):
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super().__init__("fcWp")
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self.dict_data = dict_data
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def setDictData(self, dict_data):
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self.dict_data = dict_data
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def getDictData(self):
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return self.dict_data
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@classmethod
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def load(cls, data):
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inst = super().load(data)
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inst.dict_data = pickle.loads( inst.data )
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return inst
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def dump(self):
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self.data = pickle.dumps (self.dict_data)
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return super().dump()
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chunk_map = {
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b"IHDR": IHDR,
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b"fcWp": DFLChunk,
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b"IEND": IEND
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}
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class DFLPNG(object):
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def __init__(self):
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self.data = b""
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self.length = 0
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self.chunks = []
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self.dfl_dict = None
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@staticmethod
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def load_raw(filename):
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try:
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with open(filename, "rb") as f:
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data = f.read()
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except:
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raise FileNotFoundError(filename)
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inst = DFLPNG()
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inst.data = data
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inst.length = len(data)
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if data[0:8] != PNG_HEADER:
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msg = "No Valid PNG header"
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raise ValueError(msg)
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chunk_start = 8
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while chunk_start < inst.length:
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(chunk_length, chunk_name) = struct.unpack("!I4s", data[chunk_start:chunk_start+8])
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chunk_end = chunk_start + chunk_length + 12
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chunk = chunk_map.get(chunk_name, Chunk).load(data[chunk_start:chunk_end])
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inst.chunks.append(chunk)
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chunk_start = chunk_end
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return inst
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@staticmethod
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def load(filename):
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try:
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inst = DFLPNG.load_raw (filename)
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inst.dfl_dict = inst.getDFLDictData()
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if inst.dfl_dict is not None:
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if 'face_type' not in inst.dfl_dict:
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inst.dfl_dict['face_type'] = FaceType.toString (FaceType.FULL)
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if 'fanseg_mask' in inst.dfl_dict:
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fanseg_mask = inst.dfl_dict['fanseg_mask']
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if fanseg_mask is not None:
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numpyarray = np.asarray( inst.dfl_dict['fanseg_mask'], dtype=np.uint8)
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inst.dfl_dict['fanseg_mask'] = cv2.imdecode(numpyarray, cv2.IMREAD_UNCHANGED)
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if inst.dfl_dict == None:
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return None
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return inst
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except Exception as e:
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print(e)
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return None
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@staticmethod
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def embed_data(filename, face_type=None,
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landmarks=None,
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ie_polys=None,
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source_filename=None,
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source_rect=None,
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source_landmarks=None,
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image_to_face_mat=None,
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fanseg_mask=None,
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pitch_yaw_roll=None,
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eyebrows_expand_mod=None,
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relighted=None,
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**kwargs
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):
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if fanseg_mask is not None:
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fanseg_mask = np.clip ( (fanseg_mask*255).astype(np.uint8), 0, 255 )
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ret, buf = cv2.imencode( '.jpg', fanseg_mask, [int(cv2.IMWRITE_JPEG_QUALITY), 85] )
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if ret and len(buf) < 60000:
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fanseg_mask = buf
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else:
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io.log_err("Unable to encode fanseg_mask for %s" % (filename) )
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fanseg_mask = None
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inst = DFLPNG.load_raw (filename)
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inst.setDFLDictData ({
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'face_type': face_type,
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'landmarks': landmarks,
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'ie_polys' : ie_polys.dump() if ie_polys is not None else None,
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'source_filename': source_filename,
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'source_rect': source_rect,
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'source_landmarks': source_landmarks,
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'image_to_face_mat':image_to_face_mat,
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'fanseg_mask' : fanseg_mask,
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'pitch_yaw_roll' : pitch_yaw_roll,
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'eyebrows_expand_mod' : eyebrows_expand_mod,
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'relighted' : relighted
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})
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try:
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with open(filename, "wb") as f:
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f.write ( inst.dump() )
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except:
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raise Exception( 'cannot save %s' % (filename) )
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def embed_and_set(self, filename, face_type=None,
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landmarks=None,
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ie_polys=None,
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source_filename=None,
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source_rect=None,
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source_landmarks=None,
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image_to_face_mat=None,
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fanseg_mask=None,
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pitch_yaw_roll=None,
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eyebrows_expand_mod=None,
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relighted=None,
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**kwargs
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):
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if face_type is None: face_type = self.get_face_type()
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if landmarks is None: landmarks = self.get_landmarks()
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if ie_polys is None: ie_polys = self.get_ie_polys()
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if source_filename is None: source_filename = self.get_source_filename()
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if source_rect is None: source_rect = self.get_source_rect()
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if source_landmarks is None: source_landmarks = self.get_source_landmarks()
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if image_to_face_mat is None: image_to_face_mat = self.get_image_to_face_mat()
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if fanseg_mask is None: fanseg_mask = self.get_fanseg_mask()
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if pitch_yaw_roll is None: pitch_yaw_roll = self.get_pitch_yaw_roll()
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if eyebrows_expand_mod is None: eyebrows_expand_mod = self.get_eyebrows_expand_mod()
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if relighted is None: relighted = self.get_relighted()
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DFLPNG.embed_data (filename, face_type=face_type,
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landmarks=landmarks,
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ie_polys=ie_polys,
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source_filename=source_filename,
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source_rect=source_rect,
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source_landmarks=source_landmarks,
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image_to_face_mat=image_to_face_mat,
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fanseg_mask=fanseg_mask,
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pitch_yaw_roll=pitch_yaw_roll,
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eyebrows_expand_mod=eyebrows_expand_mod,
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relighted=relighted)
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def remove_ie_polys(self):
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self.dfl_dict['ie_polys'] = None
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def remove_fanseg_mask(self):
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self.dfl_dict['fanseg_mask'] = None
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def dump(self):
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data = PNG_HEADER
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for chunk in self.chunks:
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data += chunk.dump()
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return data
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def get_shape(self):
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for chunk in self.chunks:
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if type(chunk) == IHDR:
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c = 3 if chunk.color_type == IHDR.COLOR_TYPE_RGB else 4
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w = chunk.width
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h = chunk.height
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return (h,w,c)
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return (0,0,0)
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def get_height(self):
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for chunk in self.chunks:
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if type(chunk) == IHDR:
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return chunk.height
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return 0
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def getDFLDictData(self):
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for chunk in self.chunks:
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if type(chunk) == DFLChunk:
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return chunk.getDictData()
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return None
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def setDFLDictData (self, dict_data=None):
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for chunk in self.chunks:
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if type(chunk) == DFLChunk:
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self.chunks.remove(chunk)
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break
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if not dict_data is None:
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chunk = DFLChunk(dict_data)
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self.chunks.insert(-1, chunk)
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def get_face_type(self): return self.dfl_dict['face_type']
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def get_landmarks(self): return np.array ( self.dfl_dict['landmarks'] )
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def get_ie_polys(self): return IEPolys.load(self.dfl_dict.get('ie_polys',None))
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def get_source_filename(self): return self.dfl_dict['source_filename']
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def get_source_rect(self): return self.dfl_dict['source_rect']
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def get_source_landmarks(self): return np.array ( self.dfl_dict['source_landmarks'] )
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def get_image_to_face_mat(self):
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mat = self.dfl_dict.get ('image_to_face_mat', None)
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if mat is not None:
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return np.array (mat)
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return None
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def get_fanseg_mask(self):
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fanseg_mask = self.dfl_dict.get ('fanseg_mask', None)
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if fanseg_mask is not None:
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return np.clip ( np.array (fanseg_mask) / 255.0, 0.0, 1.0 )[...,np.newaxis]
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return None
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def get_pitch_yaw_roll(self):
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return self.dfl_dict.get ('pitch_yaw_roll', None)
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def get_eyebrows_expand_mod(self):
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return self.dfl_dict.get ('eyebrows_expand_mod', None)
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def get_relighted(self):
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return self.dfl_dict.get ('relighted', False)
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def __str__(self):
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return "<PNG length={length} chunks={}>".format(len(self.chunks), **self.__dict__)
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