v0.5.1

0.5.1

Released on November 17, 2024.

Changed

• UnversalReader to read PIL images as RGB
• UniversalReader to read numpy arrays to torch directly
• RetinaFace pre-normalization color space to RGB
• torch.cross torch.linalg.cross in 3D landmark drawer

v0.5.0

Added

• UniversalReader for loading data like PIL images, numpy arrays, torch tensors, bytes, urls, and file paths

Changed

• Enable conda virtual environment by default in Docker images
• FaceAnalyzer run method to accept various input types via image_source parameter

v0.4.2

Added

• Tensor input support for FaceAnalyzer run method
• TensorReader for transforming incoming torch tensors

v0.4.1

Changed

• postprocessor for label confidence pairs to have no offset by default
• Resize transform configs to enable antialiasing by default
• notebook to version 0.4.0 or higher
• notebook to include Action Unit and Valence Arousal predictors

v0.4.0

Added

• predictor for facial valence arousal - ELIM AL from Kim et al.
• predictor postprocessor for creating label confidence pairs

Changed

• FaceAnalyzer can run without any predictors or utilizers

v0.3.1

Added

• link to ChatGPT guide that has knowledge about facetorch

Fixed

• stuck AU predictor inference in the notebook by specifying torch version to install

v0.3.0

Added

• predictor for facial action unit detection - OpenGraphAU from Luo et al.

Changed

• facetorch version retrieval error handling to not fail the run

v0.2.4

Changed

• scope of some test fixtures from function to session

v0.2.3

Fixed

• error in detector test

Removed

• deletion of detector model in tests

v0.2.2

Fixed

• error in Google Colab demo notebook