Pasted

from keras.models import Sequential
from keras.layers.core import Dense, Activation, Dropout, Flatten
from keras.layers.convolutional import Convolution2D, MaxPooling2D
 IMAGE_SIZE = 128
print('Build model...')
model = Sequential()
# three color channels, 128x128
# 16 con filters, 3 rows, 3 columns
model.add(Convolution2D(16, 3, 3, input_shape=(3, IMAGE_SIZE, IMAGE_SIZE)))
model.add(Activation('relu'))
model.add(Flatten())
model.add(Dense(1))
model.add(Dense(3 * IMAGE_SIZE * IMAGE_SIZE))
  model.compile(loss='mse', optimizer='sgd')