Conditional Random Fields say Hello to macOS

DGM library v.1.6.0 has been just released

We are glad to present our next big release of DGM, v.1.6.0, which summarizes the v.1.5.x line with further improvements and bug fixes. This is the first cross-platform release: since now on the DGM library is available also for macOS. The binaries built for macOS High Sierra (OS X 10.13) are now available for download. See the changelog for details.

DGM is a C++ library which extends popular OpenCV by implementing various tasks in probabilistic graphical models for Conditional Random Fields. In particular, the DGM learning units include:

  • Artificial Neural Networks     
  • Random Forests Model
  • Support Vector Machines
  • Sequential Gaussian Mixture Model
  • k-Nearest Neighbors
  • Bayesin Model
  • The library is also supplied with advanced feature extraction and visulaization modules. The demo code could be run directly after installation and may serve as a base for user projects.