Tags give the ability to mark specific points in history as being important
- Sort by
- Name
- Oldest updated
- Last updated
-
v2.2.0Release v2.2.0
- !73 Fix the broken if logic in ImageQualityMeasure
- !74 Updated BATL HLDI: added rc, skin/non-skin annotations, multi-channel laoding functionalities
- !75 Alignment for LightCNN: Added an alignment method, suitable for LightCNN
- !76 remove missing bootstrap-buildout.py from MANIFEST.in
- !79 Batl hldi update: Updted batl HLDI, and skin, non-skin annotation files.
- !81 MC preprocessor: The pre-processor for multi-channel data, allowing to detect and crop faces, and extract patches from cropped images.
- !80 Patch extraction from images
- !83 Preprocessing and quality check
- !77 Added CASIA-SURF database
- !86 Batl loo protocols: Adds Leave one out protocols to the BATL HLDI.
- !87 Chalearn pad: 1. Fixed small mistake in CASIA-SURF High level PAD BD 2. Added some stuff to a preprocessor (sanity check and logging)
- !88 Added the doc on MLP training using AE embeddings
- !89 Fixed CASIA SURF
- !90 [database] added modification to high-level interface for CASIA-SURF
- !91 Resolve "fix CASIA-SURF tests"
- !95 Move bob.ip.dlib and bob.ip.facelandmarks to test dependencies
- !96 Put bob.ip packages back as run requirements
- !97 unit tests: Reverts the unit tests
- !98 Add casia fasd and an optical flow extractor
-
v2.1.0Release v2.1.0
- !68 Improve load_utils.py: * Plus some minor fixes to the frame-diff method
- !67 HLDI for the CelebA database and quality estimation script: This MR contains two contributions: 1. The High Level DB interface for the CelebA database. 2. The quality assessment script + config file allowing to estimate the quality of preprocessed CelebA images.
- !66 Added an option to exclude specific types of attacks from train set in BATL DB: This allows to exclude specific PAIs from the training set of the BATL DB. PAIs currently handled: makeup.
- !65 Updated the HLDI of BATL DB, added FunnyEyes fix, and protocol joining test and dev sets
- !64 Add support for external annotations in replaymobile
- !60 Change the API of yield_faces
- !62 Add a script for analyzing database face sizes
- added preprocessors and extractors for pulse-based PAD.
-
v2.0.0Release v2.0.0
- Added High Level Database Interface (HLDI) for MIFS database
- Annotations are added for MIFS database
- Added a VideoSparseCoding preprocessor
- Updated the documentation on anomaly detection-based PAD using Aggregated Db
- Local face detection option was added to VideoFaceCrop class, using dlib and mtcnn
- Unit tests for the classes used in IQM-GMM pad algorithm
- Added landmark detection utils
- Algorithms/classifiers are adapted to other non-face modalities
- New protocol for Aggregated Database: grandtest-train-eval
- New protocol for Aggregated Database: grandtest-mobio
- Frame Selector is now acceptable in HLDIs of all databases
- Removed bootstrap-buildout.py functionality
- Added A base PAD file class
- New protocol for Aggregated Database: grandtest-train-eval-<num_train_samples>
- bob.extension.rc used in HLDIs
- Migrated to conda-based CI
- ALL algorithms are moved to bob.pad.base package
- Fixed algorithms documentation links, pointing to bob.pad.base now.
- The documentation of the package now linked to joint documentation properly.
- Refactoring: duplicated database configs are removed
- Refactoring: removed VideoQualityMeasure, replaced with Wrapper class
- Refactoring: removed VideoLBPHistogram, replaced with Wrapper class
- Refactoring: removed unused VideoDataLoader
- Refactoring: created FaceCropAlign, replaces ImageFaceCrop + VideFaceCrop using Wrapper
- Added Spatially Enhanced Histogram option to LBPHistogram class
- Changes to the FrameDifference preprocessor: Estimate the bounding box from annotations if not available. This is usually estimated from eye annotations. Remove the unused check_face_size flag. Fixed the conda recipe !63