github/DeepFaceLab
1
0
Fork 0
mirror of https://github.com/iperov/DeepFaceLab.git synced 2025-07-06 04:52:13 -07:00
Code Issues Projects Releases Packages Wiki Activity Actions

refactoring

Browse source
This commit is contained in:
Colombo 2020-03-01 19:09:50 +04:00
parent cbff72f597
commit 757ec77e44
4 changed files with 154 additions and 228 deletions
Download patch file Download diff file Expand all files Collapse all files

22
models/Model_Quick96/Model.py
View file

@ -155,6 +155,7 @@ class QModel(ModelBase):
devices = device_config.devices
resolution = self.resolution = 96
self.face_type = FaceType.FULL
ae_dims = 128
e_dims = 128
d_dims = 64
@ -357,9 +358,6 @@ class QModel(ModelBase):
# initializing sample generators
if self.is_training:
t = SampleProcessor.Types
face_type = t.FACE_TYPE_FULL
training_data_src_path = self.training_data_src_path if not self.pretrain else self.get_pretraining_data_path()
training_data_dst_path = self.training_data_dst_path if not self.pretrain else self.get_pretraining_data_path()
@ -370,16 +368,18 @@ class QModel(ModelBase):
self.set_training_data_generators ([
SampleGeneratorFace(training_data_src_path, debug=self.is_debug(), batch_size=self.get_batch_size(),
sample_process_options=SampleProcessor.Options(random_flip=True if self.pretrain else False),
output_sample_types = [ {'types' : (t.IMG_WARPED_TRANSFORMED, face_type, t.MODE_BGR), 'data_format':nn.data_format, 'resolution':resolution, },
{'types' : (t.IMG_TRANSFORMED, face_type, t.MODE_BGR), 'data_format':nn.data_format, 'resolution': resolution, },
{'types' : (t.IMG_TRANSFORMED, face_type, t.MODE_FACE_MASK_ALL_HULL), 'data_format':nn.data_format, 'resolution': resolution } ],
output_sample_types = [ {'sample_type': SampleProcessor.SampleType.FACE_IMAGE,'warp':True, 'transform':True, 'channel_type' : SampleProcessor.ChannelType.BGR, 'face_type':self.face_type, 'data_format':nn.data_format, 'resolution': resolution},
{'sample_type': SampleProcessor.SampleType.FACE_IMAGE,'warp':False, 'transform':True, 'channel_type' : SampleProcessor.ChannelType.BGR, 'face_type':self.face_type, 'data_format':nn.data_format, 'resolution': resolution},
{'sample_type': SampleProcessor.SampleType.FACE_MASK, 'warp':False, 'transform':True, 'channel_type' : SampleProcessor.ChannelType.G, 'face_mask_type' : SampleProcessor.FaceMaskType.ALL_HULL, 'face_type':self.face_type, 'data_format':nn.data_format, 'resolution': resolution}
],
generators_count=src_generators_count ),
SampleGeneratorFace(training_data_dst_path, debug=self.is_debug(), batch_size=self.get_batch_size(),
sample_process_options=SampleProcessor.Options(random_flip=True if self.pretrain else False),
output_sample_types = [ {'types' : (t.IMG_WARPED_TRANSFORMED, face_type, t.MODE_BGR), 'data_format':nn.data_format, 'resolution':resolution},
{'types' : (t.IMG_TRANSFORMED, face_type, t.MODE_BGR), 'data_format':nn.data_format, 'resolution': resolution},
{'types' : (t.IMG_TRANSFORMED, face_type, t.MODE_FACE_MASK_ALL_HULL), 'data_format':nn.data_format, 'resolution': resolution} ],
output_sample_types = [ {'sample_type': SampleProcessor.SampleType.FACE_IMAGE,'warp':True, 'transform':True, 'channel_type' : SampleProcessor.ChannelType.BGR, 'face_type':self.face_type, 'data_format':nn.data_format, 'resolution': resolution},
{'sample_type': SampleProcessor.SampleType.FACE_IMAGE,'warp':False, 'transform':True, 'channel_type' : SampleProcessor.ChannelType.BGR, 'face_type':self.face_type, 'data_format':nn.data_format, 'resolution': resolution},
{'sample_type': SampleProcessor.SampleType.FACE_MASK, 'warp':False, 'transform':True, 'channel_type' : SampleProcessor.ChannelType.G, 'face_mask_type' : SampleProcessor.FaceMaskType.ALL_HULL, 'face_type':self.face_type, 'data_format':nn.data_format, 'resolution': resolution}
],
generators_count=dst_generators_count )
])
@ -449,10 +449,8 @@ class QModel(ModelBase):
#override
def get_MergerConfig(self):
face_type = FaceType.FULL
import merger
return self.predictor_func, (self.resolution, self.resolution, 3), merger.MergerConfigMasked(face_type=face_type,
return self.predictor_func, (self.resolution, self.resolution, 3), merger.MergerConfigMasked(face_type=self.face_type,
default_mode = 'overlay',
)