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I also cleaned up a bunch of code. I'm not sure why the
simple_object_detector was keeping track of the upsample amount,
since it can't even be passed as an argument to the constructor.
Therefore, I removed the simple_object_detector_py and the second
declaration of the hog object detector. I also changed the
view code to optionally take keyword args of color and added
a single view of a rectangle.

Finally, I added viewing of the shape parts.

Can either be a list of full_object_detections or a single
full_object_detection. I couldn't get the vector type to work
for full_object_detection due to a template error.

Fix typo as well

This includes the full_object_detection, a new struct in the same
vein as the simple_object_detector_training_options and of
course, the shape predictor classes themselves.

All of training, fitting and testing are wrapped.

This deals with converting python objects to dlib objects

Also, move the vectorize template into its own header to
stop having to declare it again in vector.

Also, change point x and y to be properties

Exposes the test method, but takes in images and bounding boxes.
Seems fairly simply to extend the API

but didn't link to the approrpiate library.

into complex valued images using any dlib functions.