cvd_models.py 文件源码

def create_model(self, model_input, num_classes=2, l2_penalty=1e-8, **unused_params):
    net = slim.conv2d(model_input, 64, [3, 3], scope='conv1_1')
    # net = slim.conv2d(net, 64, [3, 3], scope='conv1_2')
    net = slim.max_pool2d(net, [2, 2], scope='pool1')

    # net = slim.conv2d(net, 128, [3, 3], scope='conv2_1')
    # net = slim.conv2d(net, 128, [3, 3], scope='conv2_2')
    # net = slim.max_pool2d(net, [2, 2], scope='pool2')

    # net = slim.conv2d(net, 258, [3, 3], scope='conv3_1')
    # net = slim.conv2d(net, 258, [3, 3], scope='conv3_2')
    # net = slim.max_pool2d(net, [2, 2], scope='pool3')

    net = slim.flatten(net)
    output = slim.fully_connected(
        net, num_classes - 1, activation_fn=tf.nn.sigmoid,
        weights_regularizer=slim.l2_regularizer(l2_penalty))
    return {"predictions": output}