inputs = Input((75,75,2))
x = Conv2D(16, kernel_size = (3,3), padding='same')(inputs)
x = BatchNormalization()(x)
x = Activation('relu')(x)
x = MaxPooling2D((2,2))(x)
x = Dropout(0.25)(x)
x = Conv2D(32, kernel_size = (3,3), padding='same')(x)
x = BatchNormalization()(x)
x = Activation('relu')(x)
x = MaxPooling2D((2,2))(x)
x = Dropout(0.25)(x)
x = Conv2D(64, kernel_size = (3,3), padding='same')(x)
x = BatchNormalization()(x)
x = Activation('relu')(x)
x = MaxPooling2D((2,2))(x)
x = Dropout(0.25)(x)
x = GlobalMaxPooling2D()(x)
c = Dense(128)(x)
c = BatchNormalization()(c)
c = Activation('relu')(c)
c = Dropout(0.25)(c)
c = Dense(1)(c)
c = BatchNormalization()(c)
c = Activation('sigmoid')(c)

model = Model(inputs,  c)