- Dropping support for Python 2.x
- –upsample a parameter for command line face_recognition
- Drop support for Python 3.4 and add 3.8
- Blink detection example
- 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
- 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
- Fixed version numbering inside of module code.
- 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.
- 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
- 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
- Added –show-distance to cli
- Fixed a bug where –tolerance was ignored in cli if testing a single image
- Added benchmark.py to examples
- Added –tolerance to cli
- 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.
- Fixed a ValueError crash when using the CLI on Python 2.7
- Raspberry Pi support.
- Fixed: Face landmarks wasn’t returning all chin points.
- Fixed a minor bug in the command-line interface.
- Minor pref improvements with face comparisons.
- Test updates.
- Fix minimum scipy version required.
- Fix missing Pillow dependency.
- First working release.