include some extra data to validate the state of the object.

they are compatible.  This was done in a way that is backwards compatible with
previous versions of dlib.  That is, we can still load data serialized by
previous dlib versions.  However, older versions of dlib can't load the new
serialization format.

matrices of float values.

out what the transformation matrix is.

for ranking functions which output constant values.

pixel types without any information loss.

images with unsigned char pixels.

Previously, we used an ASCII based format.  It now uses a much more efficient
binary format.  The deserialization routines have been made backwards
compatible with the previous format.  So dlib can still deserialize older data
but older software won't be able to read the new format.

recent changes make its feature representation incompatible with
previous versions.

since some detection templates may be larger than others and therefore
naturally accumulate larger scores, therefore necessitating larger threshold
values.

validation routines set the detection threshold to negative infinity in an
attempt to elicit all the possible detections for the purpose of computing mean
average precision scores.  This works fine when using the scan_image_boxes
object but causes the detection quality to degrade when the scan_image_pyramid
is used since this object performs random subsampling to avoid producing an
excessive number of detections.  The fix is to allow the user to set the
adjust_threshold parameter themselves to whatever value they feel is reasonable
rather than hard coding it to negative infinity.