Reorganizing the trainer

parent 1db6d460
......@@ -49,11 +49,11 @@ def main():
train_objects = db_casia.objects(groups="world")
#train_objects = db.objects(groups="world")
train_labels = [int(o.client_id) for o in train_objects]
directory = "/idiap/resource/database/CASIA-WebFace/CASIA-WebFace"
directory = "/idiap/temp/tpereira/DEEP_FACE/CASIA_WEBFACE/casia_webface/preprocessed"
train_file_names = [o.make_path(
directory=directory,
extension="")
extension=".hdf5")
for o in train_objects]
#train_data_shuffler = TripletWithSelectionDisk(train_file_names, train_labels,
......@@ -61,12 +61,12 @@ def main():
# batch_size=BATCH_SIZE)
train_data_shuffler = TripletWithFastSelectionDisk(train_file_names, train_labels,
input_shape=[125, 125, 3],
input_shape=[224, 224, 3],
batch_size=BATCH_SIZE)
# Preparing train set
directory = "/idiap/temp/tpereira/DEEP_FACE/CASIA/preprocessed"
directory = "/idiap/temp/tpereira/DEEP_FACE/CASIA_WEBFACE/mobio/preprocessed"
validation_objects = db_mobio.objects(protocol="male", groups="dev")
validation_labels = [o.client_id for o in validation_objects]
......@@ -76,7 +76,7 @@ def main():
for o in validation_objects]
validation_data_shuffler = TripletDisk(validation_file_names, validation_labels,
input_shape=[125, 125, 3],
input_shape=[224, 224, 3],
batch_size=VALIDATION_BATCH_SIZE)
# Preparing the architecture
# LENET PAPER CHOPRA
......
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