The release 1.2.0 of the Bob signal-processing and machine learning toolbox is now available
Bob provides both efficient implementations of several machine learning algorithms as well as a framework to help researchers to publish reproducible research.
It is developed by the Biometrics Group at Idiap in Switzerland.
The previous release of Bob was providing:
- image, video and audio IO interfaces such as jpg, avi, wav,
- database accessors such as FRGC, Labelled Face in the Wild, and many others,
- machines and trainers such as Support Vector Machines (SVMs), k-Means,
Probabilistic Linear Discriminant Analysis (PLDA).
The new release of Bob has brought the following features and/or improvements, such as:
This release represents a major milestone in Bob with plenty of functionality improvements (>640 commits in total: https://github.com/idiap/bob/compare/v1.1.0...v1.2.0 ) and plenty of bug fixes (https://github.com/idiap/bob/issues?page=1&state=closed ).
For instructions on how to install pre-packaged version on Ubuntu or OSX, consult our quick installation instructions: https://github.com/idiap/bob/wiki/Packages (N.B. OS X macport has not yet been upgraded. This will be done very soon. cf. https://trac.macports.org/ticket/39831 ).
The new release of Bob has brought the following features and/or improvements, such as:
- Unified implementation of Local Binary Patterns (LBPs),
- Histograms of Oriented Gradients (HOG) implementation,
- Total variability (i-vector) implementation,
- Conjugate gradient based-implementation for logistic regression,
- Improved multi-layer perceptrons implementation (Back-propagation can now be easily used in combination with any optimizer -- i.e L-BFGS),
- Pseudo-inverse-based method for Linear Discriminant Analysis,
- Covariance-based method for Principal Component Analysis,
- Whitening and within-class covariance normalization techniques,
- Module for object detection and keypoint localization (bob.visioner),
- Module for audio processing such as LFCC and MFCC,
- Improved extensions (satellite packages), that now support both Python and C++ code, within an easy to use framework,
- Improved documentation and add new tutorials,
- Support for Intel's MKL (in addition to ATLAS),
- Extend supported platforms (Arch Linux).
This release represents a major milestone in Bob with plenty of functionality improvements (>640 commits in total: https://github.com/idiap/bob/compare/v1.1.0...v1.2.0 ) and plenty of bug fixes (https://github.com/idiap/bob/issues?page=1&state=closed ).
- Sources and Documentation: https://github.com/idiap/bob/wiki/Releases
- Binary packages (instructions: https://github.com/idiap/bob/wiki/Packages ):
- Ubuntu: 10.04, 12.04, 12.10 and 13.04
- For Mac OSX: works with 10.6 (Snow Leopard), 10.7 (Lion) and 10.8 (Mountain Lion)
For instructions on how to install pre-packaged version on Ubuntu or OSX, consult our quick installation instructions: https://github.com/idiap/bob/wiki/Packages (N.B. OS X macport has not yet been upgraded. This will be done very soon. cf. https://trac.macports.org/ticket/39831 ).