dlib 18.10

Modern C++ library with a focus on portability and program correctness
dlib is a powerful library that has a large focus on portability as well as application correctness.

dlib includes a platform abstraction layer for common tasks such as interfacing with network services, handling threads, or creating graphical user interfaces.

NOTE: dlib is licensed and distributed under the terms of the Boost Software License (BSL1.0).

Main features:

  • Very portable
  • All non ISO C++ code is located in the OS abstraction layers which are as small as possible (about 9% of the library). The rest of the objects in the library are either layered on top of the OS abstraction layer or are pure ISO C++.
  • Big/little endian agnostic.
  • No assumptions are made about structure byte packing.
  • Many container classes. What makes these containers different from what can be found in the STL is how they move objects into and out of themselves. Rather than copying things around everything is moved around by swapping. This allows you to do things like have containers of containers of containers. They also have simpler interfaces.
  • There are many versions of each container with different performance characteristics so you have great flexibility in choosing exactly what you want.
  • Many of the containers perform all their allocations through the memory_manager object and unlike the STL there is no requirement that different instances of the memory manager/allocator be able to free objects allocated from each other. This allows for much more interesting memory manager implementations.
  • All containers are serializable.

last updated on:
August 30th, 2014, 18:09 GMT
file size:
5.9 MB
price:
FREE!
developed by:
Davis King
license type:
Freeware
operating system(s):
Mac OS X
binary format:
-
category:
Home \ Development \ Libraries

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dlib
What's New in This Release:
  • New Features:
  • Added find_similarity_transform()
  • Added the ability to upgrade a auto_mutex_readonly from a readonly lock to a write lock.
  • Added an implementation of the paper "One Millisecond Face Alignment with an Ensemble of Regression Trees" by Vahid Kazemi and Josephine Sullivan which appeared in this year's CVPR conference. Therefore, dlib now includes tools for learning shape models and also comes with a state-of-the-art face landmark locator. See the face_landmark_detection_ex.cpp and train_shape_predictor_ex.cpp example programs for an introduction.
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