History

1.2.3 (2018-08-21)

  • You can now pass model=”small” to face_landmarks() to use the 5-point face model instead of the 68-point model.
  • Now officially supporting Python 3.7
  • New example of using this library in a Jupyter Notebook

1.2.2 (2018-04-02)

  • Added the face_detection CLI command
  • Removed dependencies on scipy to make installation easier
  • Cleaned up KNN example and fixed a bug with drawing fonts to label detected faces in the demo

1.2.1 (2018-02-01)

  • Fixed version numbering inside of module code.

1.2.0 (2018-02-01)

  • Fixed a bug where batch size parameter didn’t work correctly when doing batch face detections on GPU.
  • Updated OpenCV examples to do proper BGR -> RGB conversion
  • Updated webcam examples to avoid common mistakes and reduce support questions
  • Added a KNN classification example
  • Added an example of automatically blurring faces in images or videos
  • Updated Dockerfile example to use dlib v19.9 which removes the boost dependency.

1.1.0 (2017-09-23)

  • Will use dlib’s 5-point face pose estimator when possible for speed (instead of 68-point face pose esimator)
  • dlib v19.7 is now the minimum required version
  • face_recognition_models v0.3.0 is now the minimum required version

1.0.0 (2017-08-29)

  • Added support for dlib’s CNN face detection model via model=”cnn” parameter on face detecion call
  • Added support for GPU batched face detections using dlib’s CNN face detector model
  • Added find_faces_in_picture_cnn.py to examples
  • Added find_faces_in_batches.py to examples
  • Added face_rec_from_video_file.py to examples
  • dlib v19.5 is now the minimum required version
  • face_recognition_models v0.2.0 is now the minimum required version

0.2.2 (2017-07-07)

  • Added –show-distance to cli
  • Fixed a bug where –tolerance was ignored in cli if testing a single image
  • Added benchmark.py to examples

0.2.1 (2017-07-03)

  • Added –tolerance to cli

0.2.0 (2017-06-03)

  • The CLI can now take advantage of multiple CPUs. Just pass in the -cpus X parameter where X is the number of CPUs to use.
  • Added face_distance.py example
  • Improved CLI tests to actually test the CLI functionality
  • Updated facerec_on_raspberry_pi.py to capture in rgb (not bgr) format.

0.1.14 (2017-04-22)

  • Fixed a ValueError crash when using the CLI on Python 2.7

0.1.13 (2017-04-20)

  • Raspberry Pi support.

0.1.12 (2017-04-13)

  • Fixed: Face landmarks wasn’t returning all chin points.

0.1.11 (2017-03-30)

  • Fixed a minor bug in the command-line interface.

0.1.10 (2017-03-21)

  • Minor pref improvements with face comparisons.
  • Test updates.

0.1.9 (2017-03-16)

  • Fix minimum scipy version required.

0.1.8 (2017-03-16)

  • Fix missing Pillow dependency.

0.1.7 (2017-03-13)

  • First working release.