def main(_):
if not FLAGS.dataset_dir:
raise ValueError(
'You must supply the dataset directory with --dataset_dir')
print('Dataset directory:', FLAGS.dataset_dir)
print('Output directory:', FLAGS.output_dir)
pascalvoc_to_tfrecords.run(FLAGS.dataset_dir, FLAGS.output_dir,
FLAGS.output_name)
def main(_):
if not FLAGS.dataset_dir:
raise ValueError('You must supply the dataset directory with --dataset_dir')
print('Dataset directory:', FLAGS.dataset_dir)
print('Output directory:', FLAGS.output_dir)
if FLAGS.dataset_name == 'pascalvoc':
pascalvoc_to_tfrecords.run(FLAGS.dataset_dir, FLAGS.output_dir, FLAGS.output_name)
else:
raise ValueError('Dataset [%s] was not recognized.' % FLAGS.dataset_name)
def main(_):
if not FLAGS.dataset_dir:
raise ValueError('You must supply the dataset directory with --dataset_dir')
print('Dataset directory:', FLAGS.dataset_dir)
print('Output directory:', FLAGS.output_dir)
if FLAGS.dataset_name == 'pascalvoc':
pascalvoc_to_tfrecords.run(FLAGS.dataset_dir, FLAGS.output_dir, FLAGS.output_name)
else:
raise ValueError('Dataset [%s] was not recognized.' % FLAGS.dataset_name)
def main(_):
gpu_options = tf.GPUOptions(allow_growth=True)
config = tf.ConfigProto(log_device_placement=False,
gpu_options=gpu_options)
sess = tf.Session(config=config)
rdn = RDN(sess,
is_train=FLAGS.is_train,
is_eval=FLAGS.is_eval,
image_size=FLAGS.image_size,
noise_level=FLAGS.noise_level,
c_dim=FLAGS.c_dim,
batch_size=FLAGS.batch_size,
D=FLAGS.D,
C=FLAGS.C,
G=FLAGS.G,
G0=FLAGS.G0,
kernel_size=FLAGS.kernel_size)
if (rdn.is_train):
rdn.train(FLAGS)
else:
if rdn.is_eval:
rdn.eval(FLAGS)
dataset_dir = os.path.join(
os.path.join(os.getcwd(), FLAGS.result_dir),
'%s_sigma/' % FLAGS.noise_level)
output_eval_path = os.path.join(os.path.join(os.getcwd(), 'Data'),
FLAGS.eval_set)
output_eval_path = output_eval_path + '/sigma_%s' % FLAGS.noise_level
if not os.path.exists(output_eval_path):
os.makedirs(output_eval_path)
pascalvoc_to_tfrecords.run(dataset_dir, output_eval_path,
'voc_2007_test')
eval_logdir = os.path.join(os.path.join(os.getcwd(), 'logs'),
'%d_sigma' % FLAGS.noise_level)
output_eval_path = output_eval_path + '/'
ssd_network.ssd_eval('pascalvoc_2007',
dataset_dir=output_eval_path,
batch_size=FLAGS.batch_size,
eval_dir=eval_logdir)
else:
# Testing the whole model
# testing is first done on RDN network
# rdn.test(FLAGS)
# Then, testing the images on SSD network for object detection
# test_path = os.path.join(os.path.join(os.getcwd(), 'Test'), FLAGS.test_set)
test_path = os.path.join(os.getcwd(), FLAGS.result_dir, 'test')
ssd_network.ssd_test(test_path)
def main(_):
print('Dataset root dir:', FLAGS.dataset_root)
print('Output directory:', FLAGS.output_dir)
if FLAGS.dataset_name == 'pascalvoc':
pascalvoc_to_tfrecords.run(FLAGS.dataset_root,
FLAGS.year,
FLAGS.split,
FLAGS.output_dir,
shuffling=True)
elif FLAGS.dataset_name == 'kitti':
kitti_object_to_tfrecords.run(FLAGS.dataset_root,
FLAGS.split,
FLAGS.output_dir,
shuffling=True)
else:
raise ValueError('Dataset [%s] was not recognized.' % FLAGS.dataset_name)
def main(_):
print('Dataset root dir:', FLAGS.dataset_root)
print('Output directory:', FLAGS.output_dir)
if FLAGS.dataset_name == 'pascalvoc':
pascalvoc_to_tfrecords.run(FLAGS.dataset_root,
FLAGS.year,
FLAGS.split,
FLAGS.output_dir,
shuffling=True)
elif FLAGS.dataset_name == 'kitti':
kitti_object_to_tfrecords.run(FLAGS.dataset_root,
FLAGS.split,
FLAGS.output_dir,
shuffling=True)
else:
raise ValueError('Dataset [%s] was not recognized.' % FLAGS.dataset_name)
def main(_):
if not FLAGS.dataset_dir:
raise ValueError(
'You must supply the dataset directory with --dataset_dir')
print('Dataset directory:', FLAGS.dataset_dir)
print('Output directory:', FLAGS.output_dir)
if FLAGS.dataset_name == 'pascalvoc':
pascalvoc_to_tfrecords.run(FLAGS.dataset_dir, FLAGS.output_dir,
FLAGS.output_name)
elif FLAGS.dataset_name == 'kitti':
if FLAGS.need_validation_split == 'True':
kitti_to_tfrecords.run(dataset_dir=FLAGS.dataset_dir,
output_dir=FLAGS.output_dir,
name=FLAGS.output_name,
need_validation_split=True)
else:
kitti_to_tfrecords.run(dataset_dir=FLAGS.dataset_dir,
output_dir=FLAGS.output_dir,
name=FLAGS.output_name,
need_validation_split=False)
else:
raise ValueError('Dataset [%s] was not recognized.' %
FLAGS.dataset_name)
