The new Dlib 19.7 Release has been announced and is now available for download. This new version comes with several improvements, new features and bug fixes over previous releases.
Dlib is a free and open source machine learning toolkit. It is written in modern C++ an contains a collection of machine learning algorithms. It is ideal for use in developing simple to complex C++ based software to solve real world problems in domains such as robotics, mobile computing, embedded systems, high performance computing environments and more.
What’s Included in the Dlib 19.7 Release
There are bug fixes centered around the input_rgb_image_pyramid::image_contained_point() function. This bug caused the function to erroneously indicate that a point wasn’t inside the original image when really it was. This caused error messages.
Also fixed is a bug where mmod_options would pick bad window sizes in some cases. There is also a fix where the extract layer that triggered when a tensor with a different number of samples than the tensor used to initialize the network was passed through the layer.
Finally also silently fixed is the loss_per_missed_target parameter of the loss_mmod_ which was not being used right when boxes were auto-ignored .
New features in this version that are centered around Deep learning. CNN+MMOD detectors have now doubled in speed as well as it now being a multi-class detector.
There are now improvements in the imglab tool that center around usability. There is also a new five point landmarking model which is faster and works with HOG and CNN. This makes it the preferred landmarking model to use.
Raw pointers can now be used in sub_images of anything. std::chrono::high_resolution_clock is now implemented and therefore it supports much higher precision. Chinese whispers clustering has now been exposed to Python.
To get your hand dirty right away you may head on over to the official website here and download the latest copy of this toolkit.
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