CalvinBackup/iperov-DeepFaceLab
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

refactoring

Browse Source
This commit is contained in:
Colombo
2020-03-08 23:19:04 +04:00
parent 121c0cfc0f
commit eda6433936
5 changed files with 9 additions and 13 deletions
Download Patch File Download Diff File Expand all files Collapse all files
samplelib/SampleGeneratorBase.py
+1 -5
View File
@@ -6,11 +6,7 @@ You can implement your own SampleGenerator
class SampleGeneratorBase(object): class SampleGeneratorBase(object):
def __init__ (self, samples_path, debug=False, batch_size=1): def __init__ (self, debug=False, batch_size=1):
if samples_path is None:
raise Exception('samples_path is None')
self.samples_path = Path(samples_path)
self.debug = debug self.debug = debug
self.batch_size = 1 if self.debug else batch_size self.batch_size = 1 if self.debug else batch_size
self.last_generation = None self.last_generation = None
samplelib/SampleGeneratorFace.py
+2 -2
View File
@@ -30,7 +30,7 @@ class SampleGeneratorFace(SampleGeneratorBase):
raise_on_no_data=True, raise_on_no_data=True,
**kwargs): **kwargs):
super().__init__(samples_path, debug, batch_size) super().__init__(debug, batch_size)
self.sample_process_options = sample_process_options self.sample_process_options = sample_process_options
self.output_sample_types = output_sample_types self.output_sample_types = output_sample_types
self.add_sample_idx = add_sample_idx self.add_sample_idx = add_sample_idx
@@ -40,7 +40,7 @@ class SampleGeneratorFace(SampleGeneratorBase):
else: else:
self.generators_count = max(1, generators_count) self.generators_count = max(1, generators_count)
samples = SampleLoader.load (SampleType.FACE, self.samples_path) samples = SampleLoader.load (SampleType.FACE, samples_path)
self.samples_len = len(samples) self.samples_len = len(samples)
self.initialized = False self.initialized = False
samplelib/SampleGeneratorFacePerson.py
+2 -2
View File
@@ -26,14 +26,14 @@ class SampleGeneratorFacePerson(SampleGeneratorBase):
person_id_mode=1, person_id_mode=1,
**kwargs): **kwargs):
super().__init__(samples_path, debug, batch_size) super().__init__(debug, batch_size)
self.sample_process_options = sample_process_options self.sample_process_options = sample_process_options
self.output_sample_types = output_sample_types self.output_sample_types = output_sample_types
self.person_id_mode = person_id_mode self.person_id_mode = person_id_mode
raise NotImplementedError("Currently SampleGeneratorFacePerson is not implemented.") raise NotImplementedError("Currently SampleGeneratorFacePerson is not implemented.")
samples_host = SampleLoader.mp_host (SampleType.FACE, self.samples_path) samples_host = SampleLoader.mp_host (SampleType.FACE, samples_path)
samples = samples_host.get_list() samples = samples_host.get_list()
self.samples_len = len(samples) self.samples_len = len(samples)
samplelib/SampleGeneratorFaceTemporal.py
+2 -2
View File
@@ -20,7 +20,7 @@ class SampleGeneratorFaceTemporal(SampleGeneratorBase):
output_sample_types=[], output_sample_types=[],
generators_count=2, generators_count=2,
**kwargs): **kwargs):
super().__init__(samples_path, debug, batch_size) super().__init__(debug, batch_size)
self.temporal_image_count = temporal_image_count self.temporal_image_count = temporal_image_count
self.sample_process_options = sample_process_options self.sample_process_options = sample_process_options
@@ -31,7 +31,7 @@ class SampleGeneratorFaceTemporal(SampleGeneratorBase):
else: else:
self.generators_count = generators_count self.generators_count = generators_count
samples = SampleLoader.load (SampleType.FACE_TEMPORAL_SORTED, self.samples_path) samples = SampleLoader.load (SampleType.FACE_TEMPORAL_SORTED, samples_path)
samples_len = len(samples) samples_len = len(samples)
if samples_len == 0: if samples_len == 0:
raise ValueError('No training data provided.') raise ValueError('No training data provided.')
samplelib/SampleGeneratorImageTemporal.py
+2 -2
View File
@@ -16,13 +16,13 @@ output_sample_types = [
''' '''
class SampleGeneratorImageTemporal(SampleGeneratorBase): class SampleGeneratorImageTemporal(SampleGeneratorBase):
def __init__ (self, samples_path, debug, batch_size, temporal_image_count, sample_process_options=SampleProcessor.Options(), output_sample_types=[], **kwargs): def __init__ (self, samples_path, debug, batch_size, temporal_image_count, sample_process_options=SampleProcessor.Options(), output_sample_types=[], **kwargs):
super().__init__(samples_path, debug, batch_size) super().__init__(debug, batch_size)
self.temporal_image_count = temporal_image_count self.temporal_image_count = temporal_image_count
self.sample_process_options = sample_process_options self.sample_process_options = sample_process_options
self.output_sample_types = output_sample_types self.output_sample_types = output_sample_types
self.samples = SampleLoader.load (SampleType.IMAGE, self.samples_path) self.samples = SampleLoader.load (SampleType.IMAGE, samples_path)
self.generator_samples = [ self.samples ] self.generator_samples = [ self.samples ]
self.generators = [iter_utils.ThisThreadGenerator ( self.batch_func, 0 )] if self.debug else \ self.generators = [iter_utils.ThisThreadGenerator ( self.batch_func, 0 )] if self.debug else \