Search Results for "image processing framework"
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Showing 50 open source projects for "image processing framework"
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ArrayFire
ArrayFire, a general purpose GPU library
ArrayFire is a general-purpose tensor library that simplifies the process of software development for the parallel architectures found in CPUs, GPUs, and other hardware acceleration devices. The library serves users in every technical computing market. Data structures in ArrayFire are smartly managed to avoid costly memory transfers and to take advantage of each performance feature provided by the underlying hardware. The community of ArrayFire developers invites you to build with us if... -
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Kornia
Open Source Differentiable Computer Vision Library
...Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within neural networks to train models to perform image transformations, epipolar geometry, depth estimation, and low-level image processing such as filtering and edge detection that operate directly on tensors. With Kornia we fill the gap between classical and deep computer vision that implements standard and advanced vision algorithms for AI. Our libraries and initiatives are always according to the community needs. -
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OpenCV
Open Source Computer Vision Library
OpenCV (Open Source Computer Vision Library) is a comprehensive open-source library for computer vision, machine learning, and image processing. It enables developers to build real-time vision applications ranging from facial recognition to object tracking. OpenCV supports a wide range of programming languages including C++, Python, and Java, and is optimized for both CPU and GPU operations. -
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BotSharp
AI Multi-Agent Framework in .NET
Conversation as a platform (CaaP) is the future, so it's perfect that we're already offering the whole toolkits to our .NET developers using the BotSharp AI BOT Platform Builder to build a CaaP. It opens up as much learning power as possible for your own robots and precisely control every step of the AI processing pipeline. BotSharp is an open source machine learning framework for AI Bot platform builder. This project involves natural language understanding, computer vision and audio processing technologies, and aims to promote the development and application of intelligent robot assistants in information systems. Out-of-the-box machine learning algorithms allow ordinary programmers to develop artificial intelligence applications faster and easier. ... -
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SAHI
A lightweight vision library for performing large object detection
...Detection of small objects and objects far away in the scene is a major challenge in surveillance applications. Such objects are represented by small number of pixels in the image and lack sufficient details, making them difficult to detect using conventional detectors. In this work, an open-source framework called Slicing Aided Hyper Inference (SAHI) is proposed that provides a generic slicing aided inference and fine-tuning pipeline for small object detection. -
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BoofCV
BoofCV is an open source Java library for real-time computer vision.
...Written from scratch for ease of use and high performance, it provides both basic and advanced features needed for creating a computer vision system. Functionality include optimized low level image processing routines (e.g. convolution, interpolation, gradient) to high level functionality such as image stabilization. Released under an Apache 2.0 license for both academic and commercial use. -
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Vision Transformer Pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA
...Because it stays close to vanilla PyTorch, you can integrate custom datasets and training loops without framework lock-in. It’s widely used as an educational reference for people learning transformers in vision and as a lightweight baseline for research prototypes. The project encourages experimentation—swap optimizers, change augmentations, or plug the transformer backbone into downstream tasks. -
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Raster Vision
Open source framework for deep learning satellite and aerial imagery
Raster Vision is an open source framework for Python developers building computer vision models on satellite, aerial, and other large imagery sets (including oblique drone imagery). There is built-in support for chip classification, object detection, and semantic segmentation using PyTorch. Raster Vision allows engineers to quickly and repeatably configure pipelines that go through core components of a machine learning workflow: analyzing training data, creating training chips, training... -
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SOD
An Embedded Computer Vision & Machine Learning Library
...Sobel operator, Otsu's binarization and over 100 image/frame processing & analysis interfaces. Designed for computational efficiency and with a strong focus on real-time applications. SOD includes a comprehensive set of both classic and state-of-the-art deep-neural networks with their pre-trained models. -
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Gluon CV Toolkit
Gluon CV Toolkit
...It features training scripts that reproduce SOTA results reported in latest papers, a large set of pre-trained models, carefully designed APIs and easy-to-understand implementations and community support. From fundamental image classification, object detection, semantic segmentation and pose estimation, to instance segmentation and video action recognition. The model zoo is the one-stop shopping center for many models you are expecting. GluonCV embraces a flexible development pattern while is super easy to optimize and deploy without retaining a heavyweight deep learning framework. -
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GIMP ML
AI for GNU Image Manipulation Program
...Additionally, operations on images such as edge detection and color clustering have also been added. GIMP-ML relies on standard Python packages such as numpy, scikit-image, pillow, pytorch, open-cv, scipy. In addition, GIMP-ML also aims to bring the benefits of using deep learning networks used for computer vision tasks to routine image processing workflows. -
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LTI-Lib is an object oriented computer vision library written in C++ for Windows/MS-VC++ and Linux/gcc. It provides lots of functionality to solve mathematical problems, many image processing algorithms, some classification tools and much more...
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opencv4nodejs
Nodejs bindings to OpenCV 3 and OpenCV 4
OpenCV4NodeJS is a Node.js binding for OpenCV, allowing developers to integrate computer vision capabilities directly into JavaScript applications for image processing, object detection, and facial recognition. -
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Mexopencv
Collection and a development kit of matlab mex functions for OpenCV
mexopencv is a collection of MEX functions that provide MATLAB bindings for OpenCV, the popular computer vision library. It enables MATLAB users to access nearly the full range of OpenCV’s C++ API directly from MATLAB, combining the ease of MATLAB scripting with the performance of OpenCV. -
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Toolbox
Piotr's Image & Video Matlab Toolbox
Piotr’s Image & Video MATLAB Toolbox is a general-purpose MATLAB toolbox for image and video processing and vision tasks, offering utilities, filters, detection, feature extraction, and algorithm building blocks. Example and demo scripts for usage (e.g. acfReadme, detector readmes). It augments MATLAB’s native capabilities (not replacing the Image Processing Toolbox) by providing efficient, reusable wrappers and optimized routines. -
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OpenPR stands for Open Pattern Recognition project and is intended to be an open source library for algorithms of image processing, computer vision, natural language processing, pattern recognition, machine learning and the related fields.
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Accord.NET Framework
Machine learning, computer vision, statistics and computing for .NET
The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building production-grade computer vision, computer audition, signal processing and statistics applications even for commercial use. A comprehensive set of sample applications provide a fast start to get up and running quickly, and extensive documentation and a wiki help fill in the details. ... -
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Accord.NET Framework
Scientific computing, machine learning and computer vision for .NET
The Accord.NET Framework provides machine learning, mathematics, statistics, computer vision, computer audition, and several scientific computing related methods and techniques to .NET. The project is compatible with the .NET Framework. NET Standard, .NET Core, and Mono. -
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Scilab Image Processing Toolbox
Advanced image processing toolbox for Scilab on Unix/Linux/Mac OS
SIP is the image processing and computer vision package for SciLab, a free Matlab-like programming environment. SIP reads/writes images in formats like JPEG, PNG, and BMP. It does filtering, segmentation, edge detection, morphology, and shape analysis. Download from Git http://siptoolbox.sourceforge.net/devel -
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R-FCN
R-FCN: Object Detection via Region-based Fully Convolutional Networks
R-FCN (“Region-based Fully Convolutional Networks”) is an object detection framework that makes almost all computation fully convolutional and shared across the image, unlike prior region-based approaches (e.g. Faster R-CNN) which run per-region sub-networks. The repository provides an implementation (in Python) supporting end-to-end training and inference of R-FCN models on standard datasets. The authors propose position-sensitive score maps to reconcile the need for translation variance (in detection) and translation invariance (in classification). ... -
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Low-power approximate adders provide basic building blocks for approximate computing hardware that have shown remarkable energy efficiency for error-resilient applications (like image/video processing, computer vision, etc.), especially for battery-driven portable systems. In this paper, we present a novel scalable, fast yet accurate analytical method to evaluate the output error probability of multi-bit low power adders for a predetermined probability of input bits. Our method recursively computes the error probability by considering the accurate cases only, which are considerably smaller than the erroneous ones. ...
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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... -
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reacTIVision is a computer vision framework for the fast and robust tracking of markers attached on physical objects, and the creation of multi-touch surfaces. It was designed for the rapid development of table-based tangible user interfaces.
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Netvlad
NetVLAD: CNN architecture for weakly supervised place recognition
NetVLAD is a deep learning-based image descriptor framework developed by Relja Arandjelović for place recognition and image retrieval. It extends standard CNNs with a trainable VLAD (Vector of Locally Aggregated Descriptors) layer to create compact, robust global descriptors from image features. This implementation includes training code and pretrained models using the Pittsburgh and Tokyo datasets. -
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Open Cezeri Library
Effective Linear Algebra and Computer Vision Library with JAVA
OCL stands for Open Cezeri Library (yet another linear algebra and matrix library). This library provides rapid coding as matlab ease of use. To learn for library please try to use test examples at OpenCezeriLibrary\test\test. It is originally developed at el-cezeri laboratory of Siirt University, in order to establish generic framework of reusable components and software tools for machine vision, machine learning, AI and robotic applications. Currently, it holds following main concepts 1-...
