# 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'):