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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
parent 7be2fd67f5
commit 046649e6be
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32 changed files with 1152 additions and 329 deletions
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68
samplelib/SampleLoader.py
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@ -1,19 +1,19 @@
import operator
import traceback
from enum import IntEnum
import cv2
import numpy as np
from pathlib import Path
from utils import Path_utils
from utils.DFLPNG import DFLPNG
from utils.DFLJPG import DFLJPG
import cv2
import numpy as np
from .Sample import Sample
from .Sample import SampleType
from facelib import FaceType
from facelib import LandmarksProcessor
from facelib import FaceType, LandmarksProcessor
from interact import interact as io
from utils import Path_utils
from utils.DFLJPG import DFLJPG
from utils.DFLPNG import DFLPNG
from .Sample import Sample, SampleType
class SampleLoader:
cache = dict()
@ -35,6 +35,10 @@ class SampleLoader:
if datas[sample_type] is None:
datas[sample_type] = SampleLoader.upgradeToFaceSamples( [ Sample(filename=filename) for filename in Path_utils.get_image_paths(samples_path) ] )
# elif sample_type == SampleType.FACE_TEMPORAL_SORTED:
# if datas[sample_type] is None:
# datas[sample_type] = SampleLoader.upgradeToFaceTemporalSortedSamples( SampleLoader.load(SampleType.FACE, samples_path) )
elif sample_type == SampleType.FACE_YAW_SORTED:
if datas[sample_type] is None:
datas[sample_type] = SampleLoader.upgradeToFaceYawSortedSamples( SampleLoader.load(SampleType.FACE, samples_path) )
@ -44,10 +48,6 @@ class SampleLoader:
if target_samples_path is None:
raise Exception('target_samples_path is None for FACE_YAW_SORTED_AS_TARGET')
datas[sample_type] = SampleLoader.upgradeToFaceYawSortedAsTargetSamples( SampleLoader.load(SampleType.FACE_YAW_SORTED, samples_path), SampleLoader.load(SampleType.FACE_YAW_SORTED, target_samples_path) )
elif sample_type == SampleType.FACE_WITH_CLOSE_TO_SELF:
if datas[sample_type] is None:
datas[sample_type] = SampleLoader.upgradeToFaceCloseToSelfSamples( SampleLoader.load(SampleType.FACE, samples_path) )
return datas[sample_type]
@ -77,44 +77,20 @@ class SampleLoader:
landmarks=dflimg.get_landmarks(),
ie_polys=dflimg.get_ie_polys(),
pitch=pitch,
yaw=yaw) )
yaw=yaw,
source_filename=dflimg.get_source_filename(),
fanseg_mask_exist=dflimg.get_fanseg_mask() is not None, ) )
except:
print ("Unable to load %s , error: %s" % (str(s_filename_path), traceback.format_exc() ) )
return sample_list
@staticmethod
def upgradeToFaceCloseToSelfSamples (samples):
yaw_samples = SampleLoader.upgradeToFaceYawSortedSamples(samples)
yaw_samples_len = len(yaw_samples)
# @staticmethod
# def upgradeToFaceTemporalSortedSamples( samples ):
# new_s = [ (s, s.source_filename) for s in samples]
# new_s = sorted(new_s, key=operator.itemgetter(1))
sample_list = []
for i in io.progress_bar_generator( range(yaw_samples_len), "Sorting"):
if yaw_samples[i] is not None:
for s in yaw_samples[i]:
s_t = []
for n in range(2000):
yaw_idx = np.clip ( i-10 +np.random.randint(20), 0, yaw_samples_len-1 )
if yaw_samples[yaw_idx] is None:
continue
yaw_idx_samples_len = len(yaw_samples[yaw_idx])
yaw_idx_sample = yaw_samples[yaw_idx][ np.random.randint(yaw_idx_samples_len) ]
if s.filename == yaw_idx_sample.filename:
continue
s_t.append ( yaw_idx_sample )
if len(s_t) >= 50:
break
if len(s_t) == 0:
s_t = [s]
sample_list.append( s.copy_and_set(close_target_list = s_t) )
return sample_list
# return [ s[0] for s in new_s]
@staticmethod
def upgradeToFaceYawSortedSamples( samples ):