v0.6.2

Released on April 17, 2026.

Fixed

• AU predictor CUDA deadlock with PyTorch >= 2.0 and CUDA >= 12.0 by loading model as native PyTorch nn.Module instead of TorchScript

Added

• Native PyTorch implementation of OpenGraphAU model (Swin Transformer backbone + GNN head)
• Support for loading native PyTorch models via native_model_class parameter in BaseModel
• timm dependency for model utilities (DropPath, to_2tuple, trunc_normal_)

Changed

• AU predictor device restored from forced CPU to configurable device (CUDA support re-enabled)

v0.6.1

Released on April 14, 2026.

Fixed

• PostArgMax post-processor to handle tuple inputs (resolves TypeError: argmax(): argument 'input' must be Tensor, not tuple)
• PostSigmoidBinary post-processor to handle tuple inputs for consistency with other post-processors

Changed

• Replaced pypi-publish and docker-push workflows with unified release workflow triggered by GitHub Release
• Switched conda CI from miniconda (classic solver) to miniforge (libmamba), reducing run time from ~60 min to ~1 min
• Updated all GitHub Actions to latest versions (checkout@v4, setup-python@v5, setup-miniconda@v3)
• Removed non-working paperswithcode badges from README for better readability

Added

• Unit tests for all post-processor tuple input handling
• Version tag validation in release workflow
• Auto-release workflow that creates GitHub Releases when version file changes on main

v0.6.0

Added

• DownloaderHuggingFace for downloading models from Hugging Face Hub

Changed

• default model download source from Google Drive to Hugging Face Hub

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