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Colombo 2019-11-24 19:51:07 +04:00
parent 1bfd65abe5
commit 77b390c04b
4 changed files with 150 additions and 25 deletions
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12
samplelib/SampleGeneratorFace.py
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@ -24,8 +24,8 @@ class SampleGeneratorFace(SampleGeneratorBase):
random_ct_samples_path=None,
sample_process_options=SampleProcessor.Options(),
output_sample_types=[],
person_id_mode=False,
add_sample_idx=False,
use_caching=False,
generators_count=2,
generators_random_seed=None,
**kwargs):
@ -34,7 +34,6 @@ class SampleGeneratorFace(SampleGeneratorBase):
self.sample_process_options = sample_process_options
self.output_sample_types = output_sample_types
self.add_sample_idx = add_sample_idx
self.person_id_mode = person_id_mode
if sort_by_yaw_target_samples_path is not None:
self.sample_type = SampleType.FACE_YAW_SORTED_AS_TARGET
@ -48,7 +47,7 @@ class SampleGeneratorFace(SampleGeneratorBase):
self.generators_random_seed = generators_random_seed
samples = SampleLoader.load (self.sample_type, self.samples_path, sort_by_yaw_target_samples_path, person_id_mode=person_id_mode)
samples = SampleLoader.load (self.sample_type, self.samples_path, sort_by_yaw_target_samples_path, use_caching=use_caching)
np.random.shuffle(samples)
self.samples_len = len(samples)
@ -149,19 +148,12 @@ class SampleGeneratorFace(SampleGeneratorBase):
if self.add_sample_idx:
batches += [ [] ]
i_sample_idx = len(batches)-1
if self.person_id_mode:
batches += [ [] ]
i_person_id = len(batches)-1
for i in range(len(x)):
batches[i].append ( x[i] )
if self.add_sample_idx:
batches[i_sample_idx].append (idx)
if self.person_id_mode:
batches[i_person_id].append ( np.array([sample.person_id]) )
break

28
samplelib/SampleGeneratorFacePerson.py
View file

@ -22,8 +22,9 @@ class SampleGeneratorFacePerson(SampleGeneratorBase):
sample_process_options=SampleProcessor.Options(),
output_sample_types=[],
person_id_mode=1,
use_caching=False,
generators_count=2,
generators_random_seed=None,
generators_random_seed=None,
**kwargs):
super().__init__(samples_path, debug, batch_size)
@ -35,15 +36,28 @@ class SampleGeneratorFacePerson(SampleGeneratorBase):
raise ValueError("len(generators_random_seed) != generators_count")
self.generators_random_seed = generators_random_seed
samples = SampleLoader.load (SampleType.FACE, self.samples_path, person_id_mode=True)
samples = SampleLoader.load (SampleType.FACE, self.samples_path, person_id_mode=True, use_caching=use_caching)
if person_id_mode==1:
new_samples = []
for s in samples:
new_samples += s
samples = new_samples
np.random.shuffle(samples)
new_samples = []
while len(samples) > 0:
for i in range( len(samples)-1, -1, -1):
sample = samples[i]
if len(sample) > 0:
new_samples.append(sample.pop(0))
if len(sample) == 0:
samples.pop(i)
samples = new_samples
#new_samples = []
#for s in samples:
# new_samples += s
#samples = new_samples
#np.random.shuffle(samples)
self.samples_len = len(samples)
if self.samples_len == 0:
@ -116,7 +130,7 @@ class SampleGeneratorFacePerson(SampleGeneratorBase):
if self.person_id_mode==1:
if len(shuffle_idxs) == 0:
shuffle_idxs = samples_idxs.copy()
np.random.shuffle(shuffle_idxs)
#np.random.shuffle(shuffle_idxs)
idx = shuffle_idxs.pop()
sample = samples[ idx ]

56
samplelib/SampleLoader.py
View file

@ -1,4 +1,5 @@
import operator
import pickle
import traceback
from enum import IntEnum
from pathlib import Path
@ -23,7 +24,7 @@ class SampleLoader:
return len ( Path_utils.get_all_dir_names(samples_path) )
@staticmethod
def load(sample_type, samples_path, target_samples_path=None, person_id_mode=False):
def load(sample_type, samples_path, target_samples_path=None, person_id_mode=True, use_caching=False):
cache = SampleLoader.cache
if str(samples_path) not in cache.keys():
@ -36,15 +37,54 @@ class SampleLoader:
datas[sample_type] = [ Sample(filename=filename) for filename in io.progress_bar_generator( Path_utils.get_image_paths(samples_path), "Loading") ]
elif sample_type == SampleType.FACE:
if datas[sample_type] is None:
if person_id_mode:
dir_names = Path_utils.get_all_dir_names(samples_path)
all_samples = []
for i, dir_name in io.progress_bar_generator( [*enumerate(dir_names)] , "Loading"):
all_samples += SampleLoader.upgradeToFaceSamples( [ Sample(filename=filename, person_id=i) for filename in Path_utils.get_image_paths( samples_path / dir_name ) ], silent=True )
datas[sample_type] = all_samples
else:
if not use_caching:
datas[sample_type] = SampleLoader.upgradeToFaceSamples( [ Sample(filename=filename) for filename in Path_utils.get_image_paths(samples_path) ] )
else:
samples_dat = samples_path / 'samples.dat'
if samples_dat.exists():
io.log_info (f"Using saved samples info from '{samples_dat}' ")
all_samples = pickle.loads(samples_dat.read_bytes())
if person_id_mode:
for samples in all_samples:
for sample in samples:
sample.filename = str( samples_path / Path(sample.filename) )
else:
for sample in all_samples:
sample.filename = str( samples_path / Path(sample.filename) )
datas[sample_type] = all_samples
else:
if person_id_mode:
dir_names = Path_utils.get_all_dir_names(samples_path)
all_samples = []
for i, dir_name in io.progress_bar_generator( [*enumerate(dir_names)] , "Loading"):
all_samples += [ SampleLoader.upgradeToFaceSamples( [ Sample(filename=filename, person_id=i) for filename in Path_utils.get_image_paths( samples_path / dir_name ) ], silent=True ) ]
datas[sample_type] = all_samples
else:
datas[sample_type] = all_samples = SampleLoader.upgradeToFaceSamples( [ Sample(filename=filename) for filename in Path_utils.get_image_paths(samples_path) ] )
if person_id_mode:
for samples in all_samples:
for sample in samples:
sample.filename = str(Path(sample.filename).relative_to(samples_path))
else:
for sample in all_samples:
sample.filename = str(Path(sample.filename).relative_to(samples_path))
samples_dat.write_bytes (pickle.dumps(all_samples))
if person_id_mode:
for samples in all_samples:
for sample in samples:
sample.filename = str( samples_path / Path(sample.filename) )
else:
for sample in all_samples:
sample.filename = str( samples_path / Path(sample.filename) )
elif sample_type == SampleType.FACE_TEMPORAL_SORTED:
if datas[sample_type] is None:
datas[sample_type] = SampleLoader.upgradeToFaceTemporalSortedSamples( SampleLoader.load(SampleType.FACE, samples_path) )