40 lines
1.3 KiB
Python
40 lines
1.3 KiB
Python
from __future__ import absolute_import
|
|
from keras.layers.core import Dense, Activation, Flatten
|
|
from keras.layers.convolutional import Conv2D, ZeroPadding2D
|
|
|
|
|
|
def layers(input_shape):
|
|
return [
|
|
ZeroPadding2D((3, 3), input_shape=input_shape, data_format='channels_first'),
|
|
Conv2D(64, (7, 7), padding='valid', data_format='channels_first'),
|
|
Activation('relu'),
|
|
|
|
ZeroPadding2D((2, 2), data_format='channels_first'),
|
|
Conv2D(64, (5, 5), data_format='channels_first'),
|
|
Activation('relu'),
|
|
|
|
ZeroPadding2D((2, 2), data_format='channels_first'),
|
|
Conv2D(64, (5, 5), data_format='channels_first'),
|
|
Activation('relu'),
|
|
|
|
ZeroPadding2D((2, 2), data_format='channels_first'),
|
|
Conv2D(48, (5, 5), data_format='channels_first'),
|
|
Activation('relu'),
|
|
|
|
ZeroPadding2D((2, 2), data_format='channels_first'),
|
|
Conv2D(48, (5, 5), data_format='channels_first'),
|
|
Activation('relu'),
|
|
|
|
ZeroPadding2D((2, 2), data_format='channels_first'),
|
|
Conv2D(32, (5, 5), data_format='channels_first'),
|
|
Activation('relu'),
|
|
|
|
ZeroPadding2D((2, 2), data_format='channels_first'),
|
|
Conv2D(32, (5, 5), data_format='channels_first'),
|
|
Activation('relu'),
|
|
|
|
Flatten(),
|
|
Dense(1024),
|
|
Activation('relu'),
|
|
]
|