Python nets.resnet_v2.resnet_v2_50() Examples

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Example #1
Source File: resnet_v2_50.py    From vehicle-triplet-reid with MIT License 5 votes vote down vote up 
def endpoints(image, is_training):
    if image.get_shape().ndims != 4:
        raise ValueError('Input must be of size [batch, height, width, 3]')

    image = image - tf.constant(_RGB_MEAN, dtype=tf.float32, shape=(1,1,1,3))

    with tf.contrib.slim.arg_scope(resnet_arg_scope(batch_norm_decay=0.9, weight_decay=0.0)):
        _, endpoints = resnet_v2_50(image, num_classes=None, is_training=is_training, global_pool=True)

    endpoints['model_output'] = endpoints['global_pool'] = tf.reduce_mean(
        endpoints['resnet_v2_50/block4'], [1, 2], name='pool5', keep_dims=False)

    return endpoints, 'resnet_v2_50'