objdet_rpn.py

from keras.models import Sequential, Model
from keras.layers import (Conv2D, Dense, GlobalAveragePooling2D, 
                          BatchNormalization, Activation, Flatten,
                          Reshape, Input)

x = Input(shape=(140,140,1))
y = Conv2D(16, (10,10), strides=(10,10), padding='valid')(x)
y = BatchNormalization()(y)
y = Activation('relu')(y)

y = Conv2D(8, (3,3), strides=(2,2), padding='same')(y)
y = BatchNormalization()(y)
y = Activation('relu')(y)

y = Conv2D(8, (3,3), padding='same')(y)
y = BatchNormalization()(y)
y = Activation('relu')(y)

# bbox prediction only
# 1 bbox = x,y,w,h,conf
z = Flatten()(y)
z = Dense(10, activation='sigmoid')(z)
z = Reshape((2,5))(z)

# region proposal network
rpn = Model(inputs=[x], outputs=[z])
rpn.summary()