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OpenCV. OpenCV ( Open Source Computer Vision Library) is a library of programming functions mainly for real-time computer vision. [ 2] Originally developed by Intel, it was later supported by Willow Garage, then Itseez (which was later acquired by Intel [ 3] ). The library is cross-platform and licensed as free and open-source software under ...
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.
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. The distribution includes data-science packages suitable for Windows, Linux, and macOS.
Python is a multi-paradigm programming language. Object-oriented programming and structured programming are fully supported, and many of their features support functional programming and aspect-oriented programming (including metaprogramming [ 70] and metaobjects ). [ 71] Many other paradigms are supported via extensions, including design by ...
The Skia Graphics Engine or Skia is an open-source 2D graphics library written in C++. Skia abstracts away platform-specific graphics APIs (which differ from one to another). [ 1] Skia Inc. originally developed the library; Google acquired it in 2005, [ 2] and then released the software as open source licensed under the New BSD free software ...
PyTorch is a machine learning library based on the Torch library, [4] [5] [6] used for applications such as computer vision and natural language processing, [7] originally developed by Meta AI and now part of the Linux Foundation umbrella.
The Computer Language Benchmarks Game site warns against over-generalizing from benchmark data, but contains a large number of micro-benchmarks of reader-contributed code snippets, with an interface that generates various charts and tables comparing specific programming languages and types of tests. [55]
Caffe (Convolutional Architecture for Fast Feature Embedding) is a deep learning framework, originally developed at University of California, Berkeley. It is open source, under a BSD license. [ 4] It is written in C++, with a Python interface. [ 5]