DeepFaceLab/utils/DFLPNG.py
Colombo 8866dce22e added
4.2.other) data_src util faceset metadata save.bat
	saves metadata of data_src\aligned\ faces into data_src\aligned\meta.dat

4.2.other) data_src util faceset metadata restore.bat
	restore metadata from 'meta.dat' to images
	if image size different from original, then it will be automatically resized

You can greatly enhance face details of src faceset by using Topaz Gigapixel software.
example https://i.imgur.com/Gwee99L.jpg
Example of workflow:
1) run 'data_src util faceset metadata save.bat'
2) launch Topaz Gigapixel
3) open 'data_src\aligned\' and select all images
4) set output folder to 'data_src\aligned_topaz' (create folder in save dialog)
5) set settings as on screenshot https://i.imgur.com/kAVWMQG.jpg
	you can choose 2x, 4x, or 6x upscale rate
6) start process images and wait full process
7) rename folders:
	data_src\aligned        ->  data_src\aligned_original
	data_src\aligned_topaz  ->  data_src\aligned
8) copy 'data_src\aligned_original\meta.dat' to 'data_src\aligned\'
9) run 'data_src util faceset metadata restore.bat'
	images will be downscaled back to original size (256x256) preserving details
	metadata will be restored
10) now your new enhanced faceset is ready to use !
2019-12-20 15:03:17 +04:00

436 lines
15 KiB
Python

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