depth_model.py 文件源码

def build(self, inputData, ss, keepProb=1):
        self.conv1_1 = self._conv_layer(inputData, params=self._params["depth/conv1_1"])
        self.conv1_2 = self._conv_layer(self.conv1_1, params=self._params["depth/conv1_2"])
        self.pool1 = self._average_pool(self.conv1_2, 'depth/pool')

        self.conv2_1 = self._conv_layer(self.pool1, params=self._params["depth/conv2_1"])
        self.conv2_2 = self._conv_layer(self.conv2_1, params=self._params["depth/conv2_2"])
        self.conv2_3 = self._conv_layer(self.conv2_2, params=self._params["depth/conv2_3"])
        self.conv2_4 = self._conv_layer(self.conv2_3, params=self._params["depth/conv2_4"])
        self.pool2 = self._average_pool(self.conv2_4, 'depth/pool')

        self.fcn1 = self._conv_layer_dropout(self.pool2, params=self._params["depth/fcn1"], keepProb=keepProb)
        self.fcn2 = self._conv_layer_dropout(self.fcn1, params=self._params["depth/fcn2"], keepProb=keepProb)

        self.outputData = self._upscore_layer(self.fcn2, params=self._params["depth/upscore"],
                                       shape=tf.shape(inputData))

        self.outputDataArgMax = tf.argmax(input=self.outputData, dimension=3)