def main(args=None):
datasets = read_data_sets()
batches = BatchRenderer(
datasets.train.images,
datasets.train.landmarks,
datasets.train.genders,
datasets.train.smiles,
datasets.train.glasses,
datasets.train.poses,
datasets.train.all_attr,
FLAGS.batch_size)
nn = CNN(
input_shape=[FLAGS.batch_size, szImg, szImg, 1],
n_filter=[20, 40, 60, 80],
n_hidden=[120],
n_y=n_y,
receptive_field=[[4, 4], [3, 3], [3, 3], [2, 2]],
pool_size=[[2, 2], [2, 2], [2, 2], [1, 1]])
nn.train(
batches,
datasets.test,
lr=FLAGS.lr,
n_epoch=FLAGS.n_epoch,
logdir=FLAGS.train_dir)
def main(args=None):
datasets = read_data_sets()
batches = BatchRenderer(
datasets.train.images,
datasets.train.landmarks,
datasets.train.genders,
datasets.train.smiles,
datasets.train.glasses,
datasets.train.poses,
datasets.train.all_attr,
FLAGS.batch_size)
nn = CSCNN(
input_shape=[FLAGS.batch_size, szImg, szImg, 1],
n_filter=[20, 40, 60, 80],
n_hidden=[120],
n_y_landmark=n_y_landmark,
n_y_attribute=n_y_attribute,
receptive_field=[[4, 4], [3, 3], [3, 3], [2, 2]],
pool_size=[[2, 2], [2, 2], [2, 2], [1, 1]],
apply_cross_stitch=[True, True, True, True, True],
apply_weight_reg=[True, True, True, True, True],
attribute=attribute,
logdir=logdir)
nn.train(
batches,
datasets.test,
lr=FLAGS.lr,
n_epoch=FLAGS.n_epoch)