diff --git a/demo/gan/gan_conf_image.py b/demo/gan/gan_conf_image.py
index 00711730d56d54ab8ef776d25c33fbf2e9445e89..83fa34fabcf83b5c55a853d2800620e086b8045a 100644
--- a/demo/gan/gan_conf_image.py
+++ b/demo/gan/gan_conf_image.py
@@ -36,9 +36,9 @@ s2, s4 = int(sample_dim/2), int(sample_dim/4),
 s8, s16 = int(sample_dim/8), int(sample_dim/16)
 
 settings(
-    batch_size=100,
-    learning_rate=1e-4,
-    learning_method=AdamOptimizer()
+    batch_size=128,
+    learning_rate=2e-4,
+    learning_method=AdamOptimizer(beta1=0.5)
 )
 
 def conv_bn(input, channels, imgSize, num_filters, output_x, stride, name, 
diff --git a/demo/gan/gan_trainer_image.py b/demo/gan/gan_trainer_image.py
index 8f1e17b9c74631b0b8d423f892c0bc44e41507ae..51bbbe8f1f4e1a860a076b41402b45a026be189b 100644
--- a/demo/gan/gan_trainer_image.py
+++ b/demo/gan/gan_trainer_image.py
@@ -88,7 +88,7 @@ def load_mnist_data(imageFile):
     for i in range(n):
         pixels = []
         for j in range(28 * 28):
-            pixels.append(float(ord(f.read(1))) / 255.0)
+            pixels.append(float(ord(f.read(1))) / 255.0 * 2.0 - 1.0)
         data[i, :] = pixels
 
     f.close()