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update == 04.20.2019 == (#242)

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* superb improved fanseg

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* added FANseg extractor for src and dst faces to use it in training

* -

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* update to 'partial' func

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* trained FANSeg_256_full_face.h5,
new experimental models: AVATAR, RecycleGAN

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* fix for TCC mode cards(tesla), was conflict with plaidML initialization.

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* update manuals

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iperov 2019-04-20 08:23:08 +04:00 • committed by GitHub
commit 046649e6be
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32 changed files with 1152 additions and 329 deletions
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54
utils/DFLJPG.py
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@ -1,9 +1,13 @@
import struct
import pickle
import struct
import cv2
import numpy as np
from facelib import FaceType
from imagelib import IEPolys
from utils.struct_utils import *
from interact import interact as io
class DFLJPG(object):
def __init__(self):
@ -137,8 +141,15 @@ class DFLJPG(object):
if type(chunk['data']) == bytes:
inst.dfl_dict = pickle.loads(chunk['data'])
if (inst.dfl_dict is not None) and ('face_type' not in inst.dfl_dict.keys()):
inst.dfl_dict['face_type'] = FaceType.toString (FaceType.FULL)
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
@ -155,9 +166,21 @@ class DFLJPG(object):
source_filename=None,
source_rect=None,
source_landmarks=None,
image_to_face_mat=None
image_to_face_mat=None,
fanseg_mask=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
inst = DFLJPG.load_raw (filename)
inst.setDFLDictData ({
'face_type': face_type,
@ -166,7 +189,8 @@ class DFLJPG(object):
'source_filename': source_filename,
'source_rect': source_rect,
'source_landmarks': source_landmarks,
'image_to_face_mat': image_to_face_mat
'image_to_face_mat': image_to_face_mat,
'fanseg_mask' : fanseg_mask,
})
try:
@ -181,7 +205,8 @@ class DFLJPG(object):
source_filename=None,
source_rect=None,
source_landmarks=None,
image_to_face_mat=None
image_to_face_mat=None,
fanseg_mask=None, **kwargs
):
if face_type is None: face_type = self.get_face_type()
if landmarks is None: landmarks = self.get_landmarks()
@ -190,14 +215,18 @@ class DFLJPG(object):
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()
DFLJPG.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)
image_to_face_mat=image_to_face_mat,
fanseg_mask=fanseg_mask)
def remove_fanseg_mask(self):
self.dfl_dict['fanseg_mask'] = None
def dump(self):
data = b""
@ -252,8 +281,13 @@ class DFLJPG(object):
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):
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
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