Dlib is a general purpose cross-platform open source software library written in the C++ programming language. Its design is heavily influenced by ideas from design by contract and component-based software engineering. This means it is, first and foremost, a collection of independent software components, each accompanied by extensive documentation and thorough debugging modes.
Since development began in 2002, dlib has grown to include a wide variety of tools. In particular, it now contains software components for dealing with networking, threads, graphical interfaces, complex data structures, linear algebra, statistical machine learning, image processing, data mining, XML and text parsing, numerical optimization, Bayesian networks, and numerous other tasks. In recent years, much of the development has been focused on creating a broad set of statistical machine learning tools. However, dlib remains a general purpose library and welcomes contributions of high quality software components useful in any domain.
Part of the development philosophy of dlib is a dedication to portability and ease of use. Therefore, all code in dlib is designed to be as portable as possible and similarly to not require a user to configure or install anything. To help achieve this, all platform specific code is confined inside the API wrappers. Everything else is either layered on top of those wrappers or is written in pure ISO standard C++. Currently the library is known to work on OS X, MS Windows, Linux, Solaris, the BSDs, and HP-UX. It should work on any POSIX platform but I haven't had the opportunity to test it on any others (if you have access to other platforms and would like to help increase this list then let me know).
The rest of this page explains everything you need to know to get started using the library. It explains where to find the documentation for each object/function and how to interpret what you find there. For help compiling with dlib check out the how to compile page. Or if you are having trouble finding where a particular object's documentation is located you may be able to find it by consulting the index.
The library is also covered by the very liberal Boost Software License so feel free to use it any way you like. However, if you use dlib in your research then please cite its Journal of Machine Learning Research paper when publishing.
Finally, I must give some credit to the Reusable Software Research Group at Ohio State since they taught me much of the software engineering techniques used in the creation of this library.
For the most part I try to document my code in a way that any C++ programmer would understand, but for the sake of brevity I use some of the following uncommon notation.
For example, you might see a line in this section that says "my_size == size()". This just means that the member variable my_size always contains the value returned by the size() function.
The library can be thought of as a collection of components. Each component always consists of at least two separate files, a specification file and an implementation file. The specification files are the ones that end with _abstract.h. Each of these specification files don't actually contain any code and they even have preprocessor directives that prevent any of their contents from being included. Their purpose is purely to document a component's interface in a file that isn't cluttered with implementation details the user shouldn't need to know about.
The next important concept in dlib organization is multi-implementation components. That is, some components provide more than one implementation of what is defined in their specification. When you use these components you have to identify them with names like dlib::component::kernel_1a. Often these components will have just a debugging and non-debugging implementation. However, many components provide a large number of alternate implementations. For example, the entropy_encoder_model has 32 different implementations you can choose from.
To create many of the objects in this library you need to choose which kernel implementation you would like and if you want the checking version or any extensions.
To make this easy there are header files which define typedefs of all this stuff. For example, to create a queue of ints using queue kernel implementation 1 you would type dlib::queue<int>::kernel_1a my_queue;. Or to get the debugging/checking version you would type dlib::queue<int>::kernel_1a_c my_queue;.
There can be a lot of different typedefs for each component. You can find a list of them in the section for the component in question. For the queue component they can be found here.
None of the above applies to the single-implementation components, that is, anything that doesn't have an "implementations" section in its documentation. These tools are designed to have only one implementation and thus do not follow the above naming convention. For example, to create a logger object you would simply type dlib::logger mylog("name");. For the purposes of object creation the API components also appear to be single-implementation. That is, there is no need to specify which implementation you want since it is automatically determined by which platform you compile under. Note also that there are no explicit checking versions of these components. However, there are DLIB_ASSERT statements that perform checking and you can enable them by #defining DEBUG or ENABLE_ASSERTS.
AssumptionsThere are some restrictions on the behavior of certain objects or functions. Rather than replicating these restrictions all over the place in my documentation they are listed here.
In the library there are three kinds of objects with regards to threading:
How do you know which components/objects are thread safe and which aren't? The rule is that if the specification for the component doesn't mention threading or thread safety then it is ok to use as long as you serialize access to shared instances. If the component might have some global resources or be reference counted then the specifications will tell you this. Lastly if the component is completely thread safe then the specification will tell you this.
Also note that global functions in dlib are always thread safe.