mobilenet_v1_1_224.py 文件源码

def endpoints(image, is_training):
    if image.get_shape().ndims != 4:
        raise ValueError('Input must be of size [batch, height, width, 3]')

    image = tf.divide(image, 255.0)

    with tf.contrib.slim.arg_scope(mobilenet_v1_arg_scope(batch_norm_decay=0.9, weight_decay=0.0)):
        _, endpoints = mobilenet_v1(image, num_classes=1001, is_training=is_training)

    endpoints['model_output'] = endpoints['global_pool'] = tf.reduce_mean(
        endpoints['Conv2d_13_pointwise'], [1, 2], name='global_pool', keep_dims=False)

    return endpoints, 'MobilenetV1'


# This is copied and modified from mobilenet_v1.py.