Change Log#

0.4.0#

Major version breaking release!#

  • This release includes numerous bug fixes, api updates, and code base changes make it largely incompatible with previous releases

  • To fork development from an older version of py-feat you can use this archival repo instead

New#

  • Added animate_face and plot_face functions in feat.plotting module

  • Fex data-classes returned from Detector.detect_image() or Detector.detect_video() now store the names of the different detectors used as attributes: .face_model, .au_model, etc

  • The AU visualization model used by plot_face and Detector.plot_detections(faces='aus') has been updated to include AU11 and remove AU18 making it consistent with Py-feat’s custom AU detectors (svm and logistic)

  • A new AU visualization model supporting the jaanet AU detector, which only has 12 AUs, has now been added and will automatically be used if Detector(au_model='jaanet').

    • This visualization model can also be used by the plot_face function by by passing it to the model argument: plot_face(model='jaanet_aus_to_landmarks')

Breaking Changes#

  • Detector no longer support unintialized models, e.g. any_model = None

    • This is is also true for Detector.change_model

  • Columns of interest on Fex data classes were previously accessed like class methods, i.e. fex.aus(). These have now been changed to class attributes, i.e. fex.aus

  • Remove support for DRML AU detector

  • Remove support for RF AU and emotion detectors

  • New default detectors:

    • svm for AUs

    • resmasknet for emotions

    • img2pose for head-pose

Development changes#

  • Revamped pre-trained detector handling in new feat.pretrained module

  • More tests including testing all detector combinations

Fixes#

0.3.7#

  • Fix import error due to missing init

0.3.6#

  • Trigger Zenodo release

0.2.0#

  • Testing pypi upload