vgg16.py 文件源码

def _image_to_head(self, is_training, reuse=None):
    with tf.variable_scope(self._scope, self._scope, reuse=reuse):
      net = slim.repeat(self._image, 2, slim.conv2d, 64, [3, 3],
                          trainable=False, scope='conv1')
      net = slim.max_pool2d(net, [2, 2], padding='SAME', scope='pool1')
      net = slim.repeat(net, 2, slim.conv2d, 128, [3, 3],
                        trainable=False, scope='conv2')
      net = slim.max_pool2d(net, [2, 2], padding='SAME', scope='pool2')
      net = slim.repeat(net, 3, slim.conv2d, 256, [3, 3],
                        trainable=is_training, scope='conv3')
      net = slim.max_pool2d(net, [2, 2], padding='SAME', scope='pool3')
      net = slim.repeat(net, 3, slim.conv2d, 512, [3, 3],
                        trainable=is_training, scope='conv4')
      net = slim.max_pool2d(net, [2, 2], padding='SAME', scope='pool4')
      net = slim.repeat(net, 3, slim.conv2d, 512, [3, 3],
                        trainable=is_training, scope='conv5')

    self._act_summaries.append(net)
    self._layers['head'] = net

    return net