Showing 5 open source projects for "image algorithm"

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  • 1
    trackers

    trackers

    Multi-object tracking algorithms

    trackers is a plug-and-play multi-object tracking library designed to work with virtually any object detection model, enabling developers to follow objects across video frames with minimal setup. The library provides clean, modular implementations of leading tracking algorithms and can be used either from the command line or embedded directly into Python pipelines. It supports inputs such as videos, webcams, RTSP streams, or image directories and produces annotated tracking outputs that...
    Downloads: 0 This Week
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  • 2
    tracking.js

    tracking.js

    A modern approach for Computer Vision on the web

    The tracking.js library brings different computer vision algorithms and techniques into the browser environment. By using modern HTML5 specifications, we enable you to do real-time color tracking, face detection and much more, all that with a lightweight core (~7 KB) and intuitive interface. To get started, download the project. This project includes all of the tracking.js examples, source code dependencies you'll need to get started. Unzip the project somewhere on your local drive. The...
    Downloads: 0 This Week
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  • 3
    CLAW is a C++ Library providing various tools in different domains, like a Tweener framework, Bézier curves manipulation, a map with multiple value types, a binary search tree container implemented as an AVL and an implementation of the sockets as std::stream. The library also includes a set of classes to easily load and write png, jpeg, gif files and other image formats. Finally, a part of the library is devoted to artificial intelligence in games and includes a generic alpha-beta algorithm. Each module is provided with an example program.
    Downloads: 2 This Week
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  • 4

    AlgART Java Libraries

    Open source library for processing arrays and matrices

    AlgART Java libraries for processing arrays and matrices are open-source product, distributed under MIT license. So, anyone can use them for free without any restrictions. Main features: 63-bit addressing of array elements (64-bit long int indexes), memory model concept (allowing storing data in different schemes from RAM to mapped disk files), wide usage of lazy evaluations, built-in multithreading optimization for multi-core processors, wide set of image processing algorithms over...
    Downloads: 0 This Week
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  • 5
    An implementation of Bruhn et al.'s fast variational optical flow algorithm using the OpenCV image processing library. The code calculates dense flow fields with a user-specified level of precision.
    Downloads: 1 This Week
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