Release Notes: This release has primarily focused on improving the flexibility and ease of use of the object detection tools.
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.
Release Notes: This release fixes a bug introduced in the previous release which could cause linker errors in some instances. It also includes usability improvements for the thread_pool and optimizations for the threaded and distributed structural svm solvers.
Release Notes: This release adds LAPACK support. In particular, now all matrix decomposition routines make use of LAPACK whenever DLIB_USE_LAPACK is #defined.
Release Notes: In addition to some minor improvements to a few tools and some additional utilities, this release adds a non-linear SVM training algorithm capable of learning from very large datasets. It also adds a tool for performing large scale manifold regularization.
Release Notes: This release was primarily devoted to bugfixes and usability improvements.
Release Notes: In addition to a lot of small usability improvements, this release adds an algorithm for performing on-line training of a support vector machine for solving classification problems.
Release Notes: This release brings support for performing QR, LU, and eigenvalue decompositions to dlib.
Release Notes: This release adds the type_safe_union object. It can be used with a dlib::pipe to create a message channel between threads that can send many different types of objects in a type safe manner. A guide for users who wish to contribute code to the library was also added to the documentation.
Release Notes: This release brings support for futures for thread synchronization. This release was also focused on improving the speed and usability of the matrix object provided by the library. Most notably, dlib is now capable of using optimized BLAS libraries to significantly speed up matrix expression evaluation.