* Add python api that generates desciptor(s) from the aligned image(s)
* Remove asserts from face_recognition.py example/tutorial
* In batch_compute_face_descriptors_from_aligned_images, use for-in loop to simplify the code
Improvde the document on binding methods and the error message if the aligned image is not of size 150x150
* Fixed reference count issue
* Fixed refcount issue in Python dlib.jitter_image and dlib.get_face_chips
* Consolidation of https://github.com/davisking/dlib/pull/1249
* Fixed build issue
* Fixed: Paths in a pytest file should be relative to dlib root
* Skip numpy return tests for Python 2.7 or if Numpy is not installed
* Enabled numpy returns tests on Python 2.7 using cPickle.dumps
* Exposed jitter_image in Python and added an example
* Return Numpy array directly
* Require numpy during setup
* Added install of Numpy before builds
* Changed pip install for user only due to security issues.
* Removed malloc
* Made presence of Numpy during compile optional.
* Conflict
* Refactored get_face_chip/get_face_chips to use Numpy as well.
In particular, these new functions don't need to be inside the face
recognition class. So I moved them out. I also fixed many incorrect
copy/pasted comments and clarified parts of the example code.
* improvements to cnn face detection interface
* mmod rectangle object renaming. possibility to set batch size in multi image detection. Added check to make sure images are all the same size.
* Add cmake option to use external libjpeg on Mac OS
* Add adjust_threshold to python object detector
* Add cmake option to use external libjpeg on Mac OS
* Add adjust_threshold to python object detector
* Revert "Add cmake option to use external libjpeg on Mac OS"
This reverts commit 01f7fd13ea.
* Update detector example to set adjust_threshold
