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refactorings

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iperov 2019-04-24 11:28:58 +04:00
commit 947feac047
11 changed files with 254 additions and 215 deletions
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12
models/Model_DEV_FANSEG/Model.py
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@ -41,19 +41,19 @@ class Model(ModelBase):
training=True)
if self.is_training_mode:
f = SampleProcessor.TypeFlags
face_type = f.FACE_TYPE_FULL if self.options['face_type'] == 'f' else f.FACE_TYPE_HALF
t = SampleProcessor.Types
face_type = t.FACE_TYPE_FULL if self.options['face_type'] == 'f' else t.FACE_TYPE_HALF
self.set_training_data_generators ([
SampleGeneratorFace(self.training_data_src_path, debug=self.is_debug(), batch_size=self.batch_size,
sample_process_options=SampleProcessor.Options(random_flip=True, motion_blur = [25, 1] ),
output_sample_types=[ [f.WARPED_TRANSFORMED | face_type | f.MODE_BGR_SHUFFLE | f.OPT_APPLY_MOTION_BLUR, self.resolution],
[f.WARPED_TRANSFORMED | face_type | f.MODE_M | f.FACE_MASK_FULL, self.resolution],
sample_process_options=SampleProcessor.Options(random_flip=True),
output_sample_types=[ { 'types': (t.IMG_WARPED_TRANSFORMED, face_type, t.MODE_BGR_SHUFFLE), 'resolution' : self.resolution, 'motion_blur':(25, 1) },
{ 'types': (t.IMG_WARPED_TRANSFORMED, face_type, t.MODE_M, t.FACE_MASK_FULL), 'resolution': self.resolution },
]),
SampleGeneratorFace(self.training_data_dst_path, debug=self.is_debug(), batch_size=self.batch_size,
sample_process_options=SampleProcessor.Options(random_flip=True ),
output_sample_types=[ [f.TRANSFORMED | face_type | f.MODE_BGR_SHUFFLE, self.resolution],
output_sample_types=[ { 'types': (t.IMG_TRANSFORMED , face_type, t.MODE_BGR_SHUFFLE), 'resolution' : self.resolution},
])
])

28
models/Model_DEV_POSEEST/Model.py
View file

@ -42,22 +42,22 @@ class Model(ModelBase):
training=True)
if self.is_training_mode:
f = SampleProcessor.TypeFlags
face_type = f.FACE_TYPE_FULL if self.options['face_type'] == 'f' else f.FACE_TYPE_HALF
t = SampleProcessor.Types
face_type = t.FACE_TYPE_FULL if self.options['face_type'] == 'f' else t.FACE_TYPE_HALF
self.set_training_data_generators ([
SampleGeneratorFace(self.training_data_src_path, debug=self.is_debug(), batch_size=self.batch_size, generators_count=4,
sample_process_options=SampleProcessor.Options( rotation_range=[0,0], motion_blur = [25, 1] ), #random_flip=True,
output_sample_types=[ [f.TRANSFORMED | face_type | f.MODE_BGR_SHUFFLE | f.OPT_APPLY_MOTION_BLUR, self.resolution ],
[f.PITCH_YAW_ROLL],
]),
SampleGeneratorFace(self.training_data_dst_path, debug=self.is_debug(), batch_size=self.batch_size, generators_count=4,
sample_process_options=SampleProcessor.Options( rotation_range=[0,0] ), #random_flip=True,
output_sample_types=[ [f.TRANSFORMED | face_type | f.MODE_BGR_SHUFFLE, self.resolution ],
[f.PITCH_YAW_ROLL],
self.set_training_data_generators ([
SampleGeneratorFace(self.training_data_src_path, debug=self.is_debug(), batch_size=self.batch_size, generators_count=4,
sample_process_options=SampleProcessor.Options( rotation_range=[0,0] ), #random_flip=True,
output_sample_types=[ {'types': (t.IMG_TRANSFORMED, face_type, t.MODE_BGR_SHUFFLE), 'resolution':self.resolution, 'motion_blur':(25, 1) },
{'types': (t.IMG_PITCH_YAW_ROLL,)}
]),
SampleGeneratorFace(self.training_data_dst_path, debug=self.is_debug(), batch_size=self.batch_size, generators_count=4,
sample_process_options=SampleProcessor.Options( rotation_range=[0,0] ), #random_flip=True,
output_sample_types=[ {'types': (t.IMG_TRANSFORMED, face_type, t.MODE_BGR_SHUFFLE), 'resolution':self.resolution },
{'types': (t.IMG_PITCH_YAW_ROLL,)}
])
])
])
#override
def onSave(self):

14
models/Model_DF/Model.py
View file

@ -44,20 +44,20 @@ class Model(ModelBase):
self.convert = K.function([ae_input_layer], rec_src)
if self.is_training_mode:
f = SampleProcessor.TypeFlags
t = SampleProcessor.Types
output_sample_types=[ { 'types': (t.IMG_WARPED_TRANSFORMED, t.FACE_TYPE_FULL, t.MODE_BGR), 'resolution':128},
{ 'types': (t.IMG_TRANSFORMED, t.FACE_TYPE_FULL, t.MODE_BGR), 'resolution':128},
{ 'types': (t.IMG_TRANSFORMED, t.FACE_TYPE_FULL, t.MODE_M, t.FACE_MASK_FULL), 'resolution':128} ]
self.set_training_data_generators ([
SampleGeneratorFace(self.training_data_src_path, sort_by_yaw_target_samples_path=self.training_data_dst_path if self.sort_by_yaw else None,
debug=self.is_debug(), batch_size=self.batch_size,
sample_process_options=SampleProcessor.Options(random_flip=self.random_flip, scale_range=np.array([-0.05, 0.05])+self.src_scale_mod / 100.0 ),
output_sample_types=[ [f.WARPED_TRANSFORMED | f.FACE_TYPE_FULL | f.MODE_BGR, 128],
[f.TRANSFORMED | f.FACE_TYPE_FULL | f.MODE_BGR, 128],
[f.TRANSFORMED | f.FACE_TYPE_FULL | f.MODE_M | f.FACE_MASK_FULL, 128] ] ),
output_sample_types=output_sample_types),
SampleGeneratorFace(self.training_data_dst_path, debug=self.is_debug(), batch_size=self.batch_size,
sample_process_options=SampleProcessor.Options(random_flip=self.random_flip),
output_sample_types=[ [f.WARPED_TRANSFORMED | f.FACE_TYPE_FULL | f.MODE_BGR, 128],
[f.TRANSFORMED | f.FACE_TYPE_FULL | f.MODE_BGR, 128],
[f.TRANSFORMED | f.FACE_TYPE_FULL | f.MODE_M | f.FACE_MASK_FULL, 128] ] )
output_sample_types=output_sample_types)
])
#override
def onSave(self):

14
models/Model_H128/Model.py
View file

@ -54,20 +54,20 @@ class Model(ModelBase):
self.dst_view = K.function([input_dst_bgr],[rec_dst_bgr, rec_dst_mask])
if self.is_training_mode:
f = SampleProcessor.TypeFlags
t = SampleProcessor.Types
output_sample_types=[ { 'types': (t.IMG_WARPED_TRANSFORMED, t.FACE_TYPE_HALF, t.MODE_BGR), 'resolution':128},
{ 'types': (t.IMG_TRANSFORMED, t.FACE_TYPE_HALF, t.MODE_BGR), 'resolution':128},
{ 'types': (t.IMG_TRANSFORMED, t.FACE_TYPE_HALF, t.MODE_M, t.FACE_MASK_FULL), 'resolution':128} ]
self.set_training_data_generators ([
SampleGeneratorFace(self.training_data_src_path, sort_by_yaw_target_samples_path=self.training_data_dst_path if self.sort_by_yaw else None,
debug=self.is_debug(), batch_size=self.batch_size,
sample_process_options=SampleProcessor.Options(random_flip=self.random_flip, scale_range=np.array([-0.05, 0.05])+self.src_scale_mod / 100.0 ),
output_sample_types=[ [f.WARPED_TRANSFORMED | f.FACE_TYPE_HALF | f.MODE_BGR, 128],
[f.TRANSFORMED | f.FACE_TYPE_HALF | f.MODE_BGR, 128],
[f.TRANSFORMED | f.FACE_TYPE_HALF | f.MODE_M | f.FACE_MASK_FULL, 128] ] ),
output_sample_types=output_sample_types ),
SampleGeneratorFace(self.training_data_dst_path, debug=self.is_debug(), batch_size=self.batch_size,
sample_process_options=SampleProcessor.Options(random_flip=self.random_flip),
output_sample_types=[ [f.WARPED_TRANSFORMED | f.FACE_TYPE_HALF | f.MODE_BGR, 128],
[f.TRANSFORMED | f.FACE_TYPE_HALF | f.MODE_BGR, 128],
[f.TRANSFORMED | f.FACE_TYPE_HALF | f.MODE_M | f.FACE_MASK_FULL, 128] ] )
output_sample_types=output_sample_types )
])
#override

14
models/Model_H64/Model.py
View file

@ -55,20 +55,20 @@ class Model(ModelBase):
self.dst_view = K.function([input_dst_bgr],[rec_dst_bgr, rec_dst_mask])
if self.is_training_mode:
f = SampleProcessor.TypeFlags
t = SampleProcessor.Types
output_sample_types=[ { 'types': (t.IMG_WARPED_TRANSFORMED, t.FACE_TYPE_HALF, t.MODE_BGR), 'resolution':64},
{ 'types': (t.IMG_TRANSFORMED, t.FACE_TYPE_HALF, t.MODE_BGR), 'resolution':64},
{ 'types': (t.IMG_TRANSFORMED, t.FACE_TYPE_HALF, t.MODE_M, t.FACE_MASK_FULL), 'resolution':64} ]
self.set_training_data_generators ([
SampleGeneratorFace(self.training_data_src_path, sort_by_yaw_target_samples_path=self.training_data_dst_path if self.sort_by_yaw else None,
debug=self.is_debug(), batch_size=self.batch_size,
sample_process_options=SampleProcessor.Options(random_flip=self.random_flip, scale_range=np.array([-0.05, 0.05])+self.src_scale_mod / 100.0 ),
output_sample_types=[ [f.WARPED_TRANSFORMED | f.FACE_TYPE_HALF | f.MODE_BGR, 64],
[f.TRANSFORMED | f.FACE_TYPE_HALF | f.MODE_BGR, 64],
[f.TRANSFORMED | f.FACE_TYPE_HALF | f.MODE_M | f.FACE_MASK_FULL, 64] ] ),
output_sample_types=output_sample_types),
SampleGeneratorFace(self.training_data_dst_path, debug=self.is_debug(), batch_size=self.batch_size,
sample_process_options=SampleProcessor.Options(random_flip=self.random_flip),
output_sample_types=[ [f.WARPED_TRANSFORMED | f.FACE_TYPE_HALF | f.MODE_BGR, 64],
[f.TRANSFORMED | f.FACE_TYPE_HALF | f.MODE_BGR, 64],
[f.TRANSFORMED | f.FACE_TYPE_HALF | f.MODE_M | f.FACE_MASK_FULL, 64] ] )
output_sample_types=output_sample_types)
])
#override

16
models/Model_LIAEF128/Model.py
View file

@ -49,22 +49,20 @@ class Model(ModelBase):
if self.is_training_mode:
f = SampleProcessor.TypeFlags
t = SampleProcessor.Types
output_sample_types=[ { 'types': (t.IMG_WARPED_TRANSFORMED, t.FACE_TYPE_FULL, t.MODE_BGR), 'resolution':128},
{ 'types': (t.IMG_TRANSFORMED, t.FACE_TYPE_FULL, t.MODE_BGR), 'resolution':128},
{ 'types': (t.IMG_TRANSFORMED, t.FACE_TYPE_FULL, t.MODE_M, t.FACE_MASK_FULL), 'resolution':128} ]
self.set_training_data_generators ([
SampleGeneratorFace(self.training_data_src_path, sort_by_yaw_target_samples_path=self.training_data_dst_path if self.sort_by_yaw else None,
debug=self.is_debug(), batch_size=self.batch_size,
sample_process_options=SampleProcessor.Options(random_flip=self.random_flip, scale_range=np.array([-0.05, 0.05])+self.src_scale_mod / 100.0 ),
output_sample_types=[ [f.WARPED_TRANSFORMED | f.FACE_TYPE_FULL | f.MODE_BGR, 128],
[f.TRANSFORMED | f.FACE_TYPE_FULL | f.MODE_BGR, 128],
[f.TRANSFORMED | f.FACE_TYPE_FULL | f.MODE_M | f.FACE_MASK_FULL, 128] ] ),
output_sample_types=output_sample_types),
SampleGeneratorFace(self.training_data_dst_path, debug=self.is_debug(), batch_size=self.batch_size,
sample_process_options=SampleProcessor.Options(random_flip=self.random_flip),
output_sample_types=[ [f.WARPED_TRANSFORMED | f.FACE_TYPE_FULL | f.MODE_BGR, 128],
[f.TRANSFORMED | f.FACE_TYPE_FULL | f.MODE_BGR, 128],
[f.TRANSFORMED | f.FACE_TYPE_FULL | f.MODE_M | f.FACE_MASK_FULL, 128] ] )
output_sample_types=output_sample_types)
])
#override

8
models/Model_RecycleGAN/Model.py
View file

@ -184,17 +184,19 @@ class RecycleGANModel(ModelBase):
if self.is_training_mode:
f = SampleProcessor.TypeFlags
t = SampleProcessor.Types
output_sample_types=[ { 'types': (t.IMG_SOURCE, t.MODE_BGR), 'resolution':resolution} ]
self.set_training_data_generators ([
SampleGeneratorImageTemporal(self.training_data_src_path, debug=self.is_debug(), batch_size=self.batch_size,
temporal_image_count=3,
sample_process_options=SampleProcessor.Options(random_flip = False, normalize_tanh = True),
output_sample_types=[ [f.SOURCE | f.MODE_BGR, resolution] ] ),
output_sample_types=output_sample_types ),
SampleGeneratorImageTemporal(self.training_data_dst_path, debug=self.is_debug(), batch_size=self.batch_size,
temporal_image_count=3,
sample_process_options=SampleProcessor.Options(random_flip = False, normalize_tanh = True),
output_sample_types=[ [f.SOURCE | f.MODE_BGR, resolution] ] ),
output_sample_types=output_sample_types ),
])
else:
self.G_convert = K.function([real_B0],[fake_A0])

10
models/Model_SAE/Model.py
View file

@ -325,12 +325,12 @@ class SAEModel(ModelBase):
self.src_sample_losses = []
self.dst_sample_losses = []
f = SampleProcessor.TypeFlags
face_type = f.FACE_TYPE_FULL if self.options['face_type'] == 'f' else f.FACE_TYPE_HALF
t = SampleProcessor.Types
face_type = t.FACE_TYPE_FULL if self.options['face_type'] == 'f' else t.FACE_TYPE_HALF
output_sample_types=[ [f.WARPED_TRANSFORMED | face_type | f.MODE_BGR, resolution] ]
output_sample_types += [ [f.TRANSFORMED | face_type | f.MODE_BGR, resolution // (2**i) ] for i in range(ms_count)]
output_sample_types += [ [f.TRANSFORMED | face_type | f.MODE_M | f.FACE_MASK_FULL, resolution // (2**i) ] for i in range(ms_count)]
output_sample_types = [ {'types' : (t.IMG_WARPED_TRANSFORMED, face_type, t.MODE_BGR), 'resolution':resolution} ]
output_sample_types += [ {'types' : (t.IMG_TRANSFORMED, face_type, t.MODE_BGR), 'resolution': resolution // (2**i) } for i in range(ms_count)]
output_sample_types += [ {'types' : (t.IMG_TRANSFORMED, face_type, t.MODE_M, t.FACE_MASK_FULL), 'resolution': resolution // (2**i) } for i in range(ms_count)]
self.set_training_data_generators ([
SampleGeneratorFace(self.training_data_src_path, sort_by_yaw_target_samples_path=self.training_data_dst_path if self.sort_by_yaw else None,