* 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
pull/1675/head
Kapil Sachdeva6 years agocommitted byDavis E. King
"If num_jitters>1 then each face will be randomly jittered slightly num_jitters times, each run through the 128D projection, and the average used as the face descriptor. "
"Optionally allows to override default padding of 0.25 around the face."
"Takes an aligned face image of size 150x150 and converts it into a 128D face descriptor."
"Note that the alignment should be done in the same way dlib.get_face_chip does it."
"If num_jitters>1 then image will be randomly jittered slightly num_jitters times, each run through the 128D projection, and the average used as the face descriptor. "
"Takes an array of images and an array of arrays of full_object_detections. `batch_faces[i]` must be an array of full_object_detections corresponding to the image `batch_img[i]`, "
"referencing faces in that image. Every face will be converting into 128D face descriptors. "
"referencing faces in that image. Every face will be converted into 128D face descriptors. "
"If num_jitters>1 then each face will be randomly jittered slightly num_jitters times, each run through the 128D projection, and the average used as the face descriptor. "
"Optionally allows to override default padding of 0.25 around the face."
"Takes an array of aligned images of faces of size 150_x_150."
"Note that the alignment should be done in the same way dlib.get_face_chip does it."
"Every face will be converted into 128D face descriptors. "
"If num_jitters>1 then each face will be randomly jittered slightly num_jitters times, each run through the 128D projection, and the average used as the face descriptor. "