rdelassus

inputs = Input(shape=(img_rows, img_cols, 3))

# encoding layers
layer0 = ZeroPadding2D(padding=(2, 2))(inputs)
layer0 = Convolution2D(50, 5, 5, border_mode='valid')(layer0)
layer0 = Activation('relu')(layer0)
layer0 = MaxPooling2D(pool_size=(pool_size, pool_size))(layer0)

layer1 = ZeroPadding2D(padding=(2, 2))(layer0)
layer1 = Convolution2D(70, 5, 5, border_mode='valid')(layer1)

rdelassus

#from __future__ import absolute_import
from keras.preprocessing.image import ImageDataGenerator, array_to_img, img_to_array, load_img

from keras.callbacks import ModelCheckpoint
from keras.models import Sequential
from keras.layers import Convolution2D, MaxPooling2D
from keras.layers import Layer, Dense, Dropout, Activation, Flatten, Reshape, Merge, Permute
from keras.layers import ZeroPadding2D, UpSampling2D
from keras.layers.normalization import BatchNormalization
import sys