# The testing mode
if FLAGS.mode == 'test':
# Check the checkpoint
if FLAGS.checkpoint is None:
raise ValueError(
'The checkpoint file is needed to performing the test.')
# In the testing time, no flip and crop is needed
if FLAGS.flip == True:
FLAGS.flip = False
if FLAGS.crop_size is not None:
FLAGS.crop_size = None
# Declare the test data reader
test_data = test_data_loader(FLAGS)
inputs_raw = tf.placeholder(tf.float32,
shape=[1, None, None, 3],
name='inputs_raw')
targets_raw = tf.placeholder(tf.float32,
shape=[1, None, None, 3],
name='targets_raw')
path_LR = tf.placeholder(tf.string, shape=[], name='path_LR')
path_HR = tf.placeholder(tf.string, shape=[], name='path_HR')
with tf.variable_scope('generator'):
if FLAGS.task == 'SRGAN' or FLAGS.task == 'SRResnet':
gen_output = generator(inputs_raw, 3, reuse=False, FLAGS=FLAGS)
else:
raise NotImplementedError('Unknown task!!')
# The testing mode
if FLAGS.mode == 'test':
# Check the checkpoint
if FLAGS.checkpoint is None:
raise ValueError('The checkpoint file is needed to performing the test.')
# In the testing time, no flip and crop is needed
if FLAGS.flip == True:
FLAGS.flip = False
if FLAGS.crop_size is not None:
FLAGS.crop_size = None
# Declare the test data reader
test_data = test_data_loader(FLAGS)
inputs_raw = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='inputs_raw')
targets_raw = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='targets_raw')
path_LR = tf.placeholder(tf.string, shape=[], name='path_LR')
path_HR = tf.placeholder(tf.string, shape=[], name='path_HR')
with tf.variable_scope('generator'):
if FLAGS.task == 'SRGAN' or FLAGS.task == 'SRResnet':
gen_output = generator(inputs_raw, 3, reuse=False, FLAGS=FLAGS)
else:
raise NotImplementedError('Unknown task!!')
print('Finish building the network')
with tf.name_scope('convert_image'):
