This change adds support to retrieve 128D face descriptor for a given
landmark. Since now we have full pipeline, README.md has "general usage"
section and integration test is added. Also, return from
FaceLandmarkDetection is changed, so it can be given to FaceRecognition
without changes. All obtained values are crosschecked to match with values
from python versions (however, if num_jitters is > 1 in FaceRecognition,
values don't match between PHP and Python, I suspect it is related to usage
of dlib::rand, but still investigating)..
This change extends existing landmark detection in new ways:
1. Existing logic is hiding HOG model (frontal_face_detector)
underneath and user cannot use other models (CNN model, for example).
2. Bounding box is exposed as additional argument, and user
can define custom bounding box (which is needed, if image used to detect
faces is changed (for example scaled), and we want to crop only face
from original image to feed into shape predictor).
3. This approach is class-based, so no need for multiple loadings of
shape predictor model (only once, in ctor)
This change extends existing landmark detection in new ways:
1. Existing logic is hiding HOG model (frontal_face_detector)
underneath and user cannot use other models (CNN model, for example).
2. Bounding box is exposed as additional argument, and user
can define custom bounding box (which is needed, if image used to detect
faces is changed (for example scaled), and we want to crop only face
from original image to feed into shape predictor).
3. This approach is class-based, so no need for multiple loadings of
shape predictor model (only once, in ctor)
Remi Collet