inception_preprocessing.py 文件源码

def preprocess_for_eval(image, height, width,
                        central_fraction=0.875, scope=None):
    """Prepare one image for evaluation.

    If height and width are specified it would output an image with that size by
    applying resize_bilinear.

    If central_fraction is specified it would cropt the central fraction of the
    input image.

    Args:
        image: 3-D Tensor of image. If dtype is tf.float32 then the range should be
            [0, 1], otherwise it would converted to tf.float32 assuming that the range
            is [0, MAX], where MAX is largest positive representable number for
            int(8/16/32) data type (see `tf.image.convert_image_dtype` for details)
        height: integer
        width: integer
        central_fraction: Optional Float, fraction of the image to crop.
        scope: Optional scope for name_scope.
    Returns:
        3-D float Tensor of prepared image.
    """
    with tf.name_scope(scope, 'eval_image', [image, height, width]):
        if image.dtype != tf.float32:
            image = tf.image.convert_image_dtype(image, dtype=tf.float32)
        # Crop the central region of the image with an area containing 87.5% of
        # the original image.
        if central_fraction:
            image = tf.image.central_crop(image, central_fraction=central_fraction)

        if height and width:
            # Resize the image to the specified height and width.
            image = tf.expand_dims(image, 0)
            image = tf.image.resize_bilinear(image, [height, width],
                                             align_corners=False)
            image = tf.squeeze(image, [0])
        image = tf.sub(image, 0.5)
        image = tf.mul(image, 2.0)
        return image