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The Open Source Computer Vision Library has >2500 algorithms, extensive documentation and sample code for real-time computer vision. It works on Windows, Linux, Mac OS X, Android, iOS in your browser through JavaScript. Languages: C++, Python, Julia, Javascript Homepage: https://opencv.org Q&A forum: https://forum.opencv.org/ Documentation: https://docs.opencv.org Source code: https://github.com/opencv Please pay special attention to our tutorials! https://docs.opencv.org/master Books about the OpenCV are described here: https://opencv.org/books.html

MSTParser is a non-projective dependency parser that searches for maximum spanning trees over directed graphs. Models of dependency structure are based on large-margin discriminative training methods. Projective parsing is also supported. mstparser 0.5.1 is now available via Maven Central. If you use Maven as your build tool, then you can add it as a dependency in your pom.xml file: <dependency> <groupId>net.sourceforge.mstparser</groupId> <artifactId>mstparser</artifactId> ...

With this Python module (based on C++ code) it is possible to create a Brain Comp. Interface (BCI) and herewith to get EEG data online and evaluate the data while receiving it. - Up to now, this tool relies on the Brain Vision Rec. as EEG software -

A mouse tracker for OS X. The tool should provide a simple way to log the user's mouse movements in the background for (later) analysis. Currently only for Mac OS X (ObjC & Cocoa), planned to make platform independent with Python. It consists out of two