main.py

import tensorflow as tf
from model import ESPCN
flags = tf.app.flags
FLAGS = flags.FLAGS
flags.DEFINE_integer("epoch", 150000, "Number of epoch")
flags.DEFINE_integer("image_size", 17, "The size of image input")
flags.DEFINE_integer("c_dim", 3, "The size of channel")
flags.DEFINE_boolean("is_train", True, "if the train")
flags.DEFINE_integer("scale", 3, "the size of scale factor for preprocessing input image")
flags.DEFINE_integer("stride", 14, "the size of stride")
flags.DEFINE_string("checkpoint_dir", "checkpoint", "Name of checkpoint directory")
flags.DEFINE_float("learning_rate", 1e-5 , "The learning rate")
flags.DEFINE_integer("batch_size", 128, "the size of batch")
flags.DEFINE_string("result_dir", "result", "Name of result directory")
flags.DEFINE_string("test_img", "", "test_img")



def main(_): #?
    with tf.Session() as sess:
        espcn = ESPCN(sess,
                      image_size = FLAGS.image_size,
                      is_train = FLAGS.is_train,
                      scale = FLAGS.scale,
                      c_dim = FLAGS.c_dim,
                      batch_size = FLAGS.batch_size,
                      test_img = FLAGS.test_img,
                      )

        espcn.train(FLAGS)

if __name__=='__main__':
    tf.app.run() # parse the command argument , the call the main function