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OpenCV runs on the desktop operating systems: Windows, Linux, macOS, FreeBSD, NetBSD and OpenBSD as well as mobile operating systems: Android, iOS, Maemo, [19] BlackBerry 10 and QNX. [20] The user can get official releases from SourceForge or take the latest sources from GitHub. [21] OpenCV uses CMake.
Python Imaging Library is a free and open-source additional library for the Python programming language that adds support for opening, manipulating, and saving many different image file formats. It is available for Windows, Mac OS X and Linux. The latest version of PIL is 1.1.7, was released in September 2009 and supports Python 1.5.2–2.7. [3]
Nuitka (pronounced as / n juː t k ʌ / [2]) is a source-to-source compiler which compiles Python code to C source code, applying some compile-time optimizations in the process such as constant folding and propagation, built-in call prediction, type inference, and conditional statement execution.
Anaconda is a distribution of the Python and R programming languages for scientific computing (data science, machine learning applications, large-scale data processing, predictive analytics, etc.), that aims to simplify package management and deployment. Anaconda distribution includes data-science packages suitable for Windows, Linux, and macOS ...
A CMake file is provided and the library is compatible with Windows, Linux and Mac OS X. The library was tested successfully with OpenCV 2.4.10. BGSLibrary includes the original LBP implementation for motion detection [ 12 ] as well as a new LBP operator variant combined with Markov Random Fields [ 13 ] with improved recognition rates and ...
ilastik allows user to annotate an arbitrary number of classes in images with a mouse interface. Using these user annotations and the generic image features, the user can train a random forest classifier.
The Lunar Owls closed out the fourth quarter on a 17-7 run, after trailing by as many as 10 points, in the only comeback win of the opening weekend. Teams with leads in the five other games played ...
With CANN backend in OpenCV DNN, giving developers ability to run created AI models on the Ascend, Kirin and other HiSilicon NPU enabled chips. [5] It supports cross platform development such as Android, iOS, Windows, [6] global OpenHarmony-based distro, Eclipse Oniro, Linux-based EulerOS alongside OpenEuler Huawei's server OS platforms, macOS ...