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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]).
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.
On April 24, 2024, Huawei's MindSpore 2.3.RC1 was released to open source community with Foundation Model Training, Full-Stack Upgrade of Foundation Model Inference, Static Graph Optimization, IT Features and new MindSpore Elec MT (MindSpore-powered magnetotelluric) Intelligent Inversion Model.
CMV, includes the general LBP implementation Archived 2014-11-28 at the Wayback Machine and many further extensions over LBP histogram in MATLAB. Python mahotas, an open source computer vision package which includes an implementation of LBPs. OpenCV's Cascade Classifiers support LBPs as of version 2.
opencv.github.io /cvat /about / Computer Vision Annotation Tool (CVAT) is an open source , web-based image and video annotation tool used for labeling data for computer vision algorithms. Originally developed by Intel , CVAT is designed for use by a professional data annotation team, with a user interface optimized for computer vision ...
PyTorch 2.0 was released on 15 March 2023, introducing TorchDynamo, a Python-level compiler that makes code run up to 2x faster, along with significant improvements in training and inference performance across major cloud platforms. [25] [26]
Pygame was originally written by Pete Shinners to replace PySDL after its development stalled. [2] [8] It has been a community project since 2000 [9] and is released under the free software GNU Lesser General Public License [5] (which "provides for Pygame to be distributed with open source and commercial software" [10]).
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 ...