def __init__(
self,
protocol,
annotation_type="eyes-center",
fixed_positions=None,
dataset_original_directory=rc.get("bob.db.meds.directory", ""),
dataset_original_extension=".jpg",
):
# Downloading model if not exists
urls = MEDSDatabase.urls()
filename = get_file("meds.tar.gz",
urls,
file_hash="3b01354d4c170672ac14120b80dace75")
super().__init__(
name="meds",
dataset_protocol_path=filename,
protocol=protocol,
csv_to_sample_loader=make_pipeline(
CSVToSampleLoaderBiometrics(
data_loader=bob.io.base.load,
dataset_original_directory=dataset_original_directory
if dataset_original_directory else "",
extension=dataset_original_extension,
),
EyesAnnotations(),
),
annotation_type=annotation_type,
fixed_positions=fixed_positions,
)
def __init__(self,
protocol,
annotation_type="eyes-center",
fixed_positions=None):
# Downloading model if not exists
urls = ARFaceDatabase.urls()
filename = get_file(
"arface.tar.gz",
urls,
file_hash="66cf05fe03adb8d73a76fd75641dd468",
)
super().__init__(
name="arface",
dataset_protocol_path=filename,
protocol=protocol,
csv_to_sample_loader=make_pipeline(
CSVToSampleLoaderBiometrics(
data_loader=bob.io.base.load,
dataset_original_directory=rc[
"bob.bio.face.arface.directory"]
if rc["bob.bio.face.arface.directory"] else "",
extension=rc["bob.bio.face.arface.extension"]
if rc["bob.bio.face.arface.extension"] else ".ppm",
),
EyesAnnotations(),
),
annotation_type=annotation_type,
fixed_positions=fixed_positions,
)
def __init__(self,
protocol,
annotation_type="eyes-center",
fixed_positions=None):
# Downloading model if not exists
urls = CasiaAfricaDatabase.urls()
filename = get_file(
"casia-africa.tar.gz",
urls,
file_hash="080d4bfffec95a6445507065054757eb",
)
directory = (rc["bob.db.casia-africa.directory"]
if rc["bob.db.casia-africa.directory "] else "")
super().__init__(
name="casia-africa",
dataset_protocol_path=filename,
protocol=protocol,
csv_to_sample_loader=make_pipeline(
CSVToSampleLoaderBiometrics(
data_loader=bob.io.base.load,
dataset_original_directory=directory,
extension=".jpg",
reference_id_equal_subject_id=False,
),
EyesAnnotations(),
),
annotation_type=annotation_type,
fixed_positions=fixed_positions,
)
def __init__(
self,
protocol,
annotation_type="eyes-center",
fixed_positions=None,
dataset_original_directory=rc.get("bob.db.morph.directory", ""),
dataset_original_extension=".JPG",
):
# Downloading model if not exists
urls = MorphDatabase.urls()
filename = get_file("morph.tar.gz",
urls,
file_hash="9efa1ff13ef6984ebfcf86f1b1f58873")
super().__init__(
name="morph",
dataset_protocol_path=filename,
protocol=protocol,
csv_to_sample_loader=make_pipeline(
CSVToSampleLoaderBiometrics(
data_loader=bob.io.base.load,
dataset_original_directory=dataset_original_directory
if dataset_original_directory else "",
extension=dataset_original_extension,
),
EyesAnnotations(),
),
annotation_type=annotation_type,
fixed_positions=fixed_positions,
)
def __init__(
self,
protocol,
annotation_type="eyes-center",
fixed_positions=None,
dataset_original_directory=rc.get("bob.db.mobio.directory", ""),
dataset_original_extension=rc.get("bob.db.mobio.extension",
".png"),
):
# Downloading model if not exists
urls = MobioDatabase.urls()
filename = get_file("mobio.tar.gz",
urls,
file_hash="4a7f99b33a54b2dd337ddcaecb09edb8")
super().__init__(
name="mobio",
dataset_protocol_path=filename,
protocol=protocol,
csv_to_sample_loader=make_pipeline(
CSVToSampleLoaderBiometrics(
data_loader=bob.io.base.load,
dataset_original_directory=dataset_original_directory,
extension=dataset_original_extension,
),
EyesAnnotations(),
),
annotation_type=annotation_type,
fixed_positions=fixed_positions,
)
def __init__(self,
protocol,
annotation_type="eyes-center",
fixed_positions=None):
# Downloading model if not exists
urls = FRGCDatabase.urls()
filename = get_file(
"frgc.tar.gz",
urls,
file_hash="242168e993fe0f6f29bd59fccf3c79a0",
)
super().__init__(
name="frgc",
dataset_protocol_path=filename,
protocol=protocol,
csv_to_sample_loader=make_pipeline(
CSVToSampleLoaderBiometrics(
data_loader=bob.io.base.load,
dataset_original_directory=rc.get(
"bob.bio.face.frgc.directory", ""),
extension="",
reference_id_equal_subject_id=False,
),
EyesAnnotations(),
),
annotation_type=annotation_type,
fixed_positions=fixed_positions,
score_all_vs_all=True,
group_probes_by_reference_id=True,
memory_demanding=True,
)
self.hash_fn = hash_string
def __init__(self,
protocol,
annotation_type="eyes-center",
fixed_positions=None):
# Downloading model if not exists
urls = CaspealDatabase.urls()
filename = get_file(
"caspeal.tar.gz",
urls,
file_hash="1c77f660ef85fa263a2312fd8263d0d9",
)
super().__init__(
name="caspeal",
dataset_protocol_path=filename,
protocol=protocol,
csv_to_sample_loader=make_pipeline(
CSVToSampleLoaderBiometrics(
data_loader=bob.io.base.load,
dataset_original_directory=rc[
"bob.bio.face.caspeal.directory"]
if rc["bob.bio.face.caspeal.directory"] else "",
extension=".png",
),
EyesAnnotations(),
),
annotation_type=annotation_type,
fixed_positions=fixed_positions,
)
def __init__(self,
protocol,
annotation_type="eyes-center",
fixed_positions=None):
# Downloading model if not exists
urls = CBSRNirVis2Database.urls()
filename = get_file(
"cbsr-nir-vis2.tar.gz",
urls,
file_hash="e4bda52ab6754556783d6730eccc2ae2",
)
directory = (rc["bob.db.cbsr-nir-vis-2.directory"]
if rc["bob.db.cbsr-nir-vis-2.directory"] else "")
def load(filename):
extensions = [".jpg", ".bmp"]
for e in extensions:
f = os.path.splitext(filename)[0]
new_filename = f + e
if os.path.exists(new_filename):
return bob.io.base.load(new_filename)
else:
raise ValueError("File `{0}` not found".format(
str(new_filename)))
super().__init__(
name="cbsr-nir-vis2",
dataset_protocol_path=filename,
protocol=protocol,
csv_to_sample_loader=make_pipeline(
CSVToSampleLoaderBiometrics(
data_loader=load,
dataset_original_directory=directory,
extension=".jpg",
),
EyesAnnotations(),
),
annotation_type=annotation_type,
fixed_positions=fixed_positions,
)
def __init__(
self, protocol, annotation_type="eyes-center", fixed_positions=None
):
# Downloading model if not exists
urls = PolaThermalDatabase.urls()
filename = get_file(
"polathermal.tar.gz",
urls,
file_hash="4693149bc883debe5a9e1441a4f5f4ae",
)
directory = rc.get("bob.db.pola-thermal.directory", "")
def load(path):
"""
Images in this dataset are stored as 16-bit PNG [0-65535]
and bob.bio.face assumes images are between 0 and 255,
so we divide by 257: 65535 / 255 = 257
"""
return bob.io.base.load(path) / 257
super().__init__(
name="polathermal",
protocol=protocol,
dataset_protocol_path=filename,
csv_to_sample_loader=make_pipeline(
CSVToSampleLoaderBiometrics(
data_loader=load,
dataset_original_directory=directory,
extension=".png",
),
EyesAnnotations(),
),
annotation_type=annotation_type,
fixed_positions=fixed_positions,
)