Merge branch 'master' of https://github.com/zsdonghao/SRGAN

Author: akaraspt

main.py

@@ -15,8 +15,6 @@
 from config import config, log_config
 
 
-# SRGAN_g = SRGAN_g2
-SRGAN_d = SRGAN_d2
 
 
 ###====================== HYPER-PARAMETERS ===========================###
@@ -218,7 +216,7 @@ def train():
             tl.files.save_npz(net_g.all_params, name=checkpoint_dir+'/g_{}_init.npz'.format(tl.global_flag['mode']), sess=sess)
 
     ###========================= train GAN (SRGAN) =========================###
-    for epoch in range(500, n_epoch+1):
+    for epoch in range(0, n_epoch+1):
         ## update learning rate
         if epoch !=0 and (epoch % decay_every == 0):
             new_lr_decay = lr_decay ** (epoch // decay_every)

model.py

@@ -109,7 +109,7 @@ def SRGAN_g2(t_image, is_train=False, reuse=False):
         return n
 
 
-def SRGAN_d(t_image, is_train=False, reuse=False):
+def SRGAN_d2(t_image, is_train=False, reuse=False):
     """ Discriminator in Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
     feature maps (n) and stride (s) feature maps (n) and stride (s)
     """
@@ -152,7 +152,7 @@ def SRGAN_d(t_image, is_train=False, reuse=False):
 
         return n, logits
 
-def SRGAN_d2(input_images, is_train=True, reuse=False):
+def SRGAN_d(input_images, is_train=True, reuse=False):
     w_init = tf.random_normal_initializer(stddev=0.02)
     b_init = None # tf.constant_initializer(value=0.0)
     gamma_init=tf.random_normal_initializer(1., 0.02)