aboutsummaryrefslogtreecommitdiff
diff options
context:
space:
mode:
-rwxr-xr-xcdcgan.py20
-rw-r--r--dcgan.py5
2 files changed, 9 insertions, 16 deletions
diff --git a/cdcgan.py b/cdcgan.py
index 7b517ca..01368ac 100755
--- a/cdcgan.py
+++ b/cdcgan.py
@@ -65,22 +65,16 @@ class CDCGAN():
model.add(Dense(128 * 7 * 7, activation="relu", input_dim=self.latent_dim))
model.add(Reshape((7, 7, 128)))
- model.add(UpSampling2D())
- for i in range(self.conv_layers):
- model.add(Conv2D(128, kernel_size=3, padding="same"))
- model.add(BatchNormalization())
- model.add(Activation("relu"))
-
- model.add(UpSampling2D())
-
- for i in range(self.conv_layers):
- model.add(Conv2D(64, kernel_size=3, padding="same"))
- model.add(BatchNormalization())
+ model.add(Conv2DTranspose(256, kernel_size=3, padding="same", strides=(2,2)))
+ model.add(BatchNormalization())
+ model.add(Activation("relu"))
- model.add(Activation("relu"))
+ model.add(Conv2DTranspose(128, kernel_size=3, padding="same", strides=(2,2)))
+ model.add(BatchNormalization())
+ model.add(Activation("relu"))
- model.add(Conv2D(self.channels, kernel_size=3, padding="same"))
+ model.add(Conv2DTranspose(64, kernel_size=3, padding="same"))
model.add(Activation("tanh"))
#model.summary()
diff --git a/dcgan.py b/dcgan.py
index 347f61e..719e096 100644
--- a/dcgan.py
+++ b/dcgan.py
@@ -1,4 +1,5 @@
from __future__ import print_function, division
+import tensorflow.keras as keras
from keras.datasets import mnist
from keras.layers import Input, Dense, Reshape, Flatten, Dropout
from keras.layers import BatchNormalization, Activation, ZeroPadding2D
@@ -75,7 +76,7 @@ class DCGAN():
model.add(Conv2D(self.channels, kernel_size=3, padding="same"))
model.add(Activation("tanh"))
- #model.summary()
+ model.summary()
noise = Input(shape=(self.latent_dim,))
img = model(noise)
@@ -187,8 +188,6 @@ class DCGAN():
fig.savefig("images/mnist_%d.png" % epoch)
plt.close()
-'''
if __name__ == '__main__':
dcgan = DCGAN()
dcgan.train(epochs=4000, batch_size=32, save_interval=50)
-'''