RSS All releases of dlib C++ Library

  •  10 Apr 2014 14:16

Release Notes: The major new feature in this release is a Python API for training histogram-of-oriented-gradient based object detectors and examples showing how to use this type of detector to perform real-time face detection. Simpler interfaces were provided for learning to solve assignment and multi-target tracking problems.

  •  04 Feb 2014 11:21

Release Notes: This release added a tool for training histogram-of-oriented-gradient based object detectors and examples showing how to use this type of detector to perform real-time face detection. It also added multi-threaded training options for the multiclass classifiers as well as numerous other usability improvements.

  •  23 Oct 2013 00:21

Release Notes: This release adds bound constrained non-linear optimizers using the BFGS and L-BFGS methods. It also includes a new tool for learning a max-margin Mahalanobis distance metric as well as routines for easily computing Felzenszwalb's 31 channel HOG image representation.

  •  29 Aug 2013 06:10

Release Notes: This release focused on improving the speed and usability of dlib's structural support vector machine solver. Two new tutorial style example programs showing how to use the solver from either C++ or Python were included.

  •  22 Jun 2013 14:34

Release Notes: This release added a tool for solving large scale support vector regression problems to the library as well as a structural SVM tool for learning BIO or BILOU style sequence tagging models. It also added Python interfaces to a number of dlib's machine learning tools.

Release Notes: This release has primarily focused on improving the flexibility and ease of use of the object detection tools.

  •  26 Mar 2013 12:47

Release Notes: In addition to some bugfixes, this release also brings the following notable improvements to the library: a more accurate SURF feature extractor, a faster cutting plane solver, a routine for computing the singular value decomposition of very large matrices, a tool for performing canonical correlation analysis on large datasets, and simple tools for writing parallel for loops.

  •  04 Feb 2013 23:51

Release Notes: This release includes a large number of new minor features and usability improvements. It also includes a new machine learning tool for learning to rank objects. This is the dlib::svm_rank_trainer, an implementation of the well known SVM-Rank algorithm. Moreover, the implementation runs in O(n*log(n)) time and is therefore suitable for use with large training datasets.

  •  19 Dec 2012 23:06

Release Notes: This release brings a number of new features to the library. Highlights include a probabilistic CKY parser, tools for creating applications using the Bulk Synchronous Parallel computing model, and two new clustering algorithms: Chinese Whispers and Newman's modularity clustering.

  •  18 Oct 2012 22:24

Release Notes: In addition to a number of minor usability and feature improvements, this release also gives dlib's object detection tools the ability to model objects with movable parts.

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