Search Results for "image processing framework"

ncnn implementation of waifu2x converter. Runs fast on Intel/AMD/Nvidia/Apple-Silicon with Vulkan API. waifu2x-ncnn-vulkan uses ncnn project as the universal neural network inference framework.

IM is a toolkit for Digital Imaging. IM is based on 4 concepts: Image Representation, Storage, Processing and Capture. The main goal of the library is to provide a simple API and abstraction of images for scientific applications.

The Related Values Processing Framework helps the integration of Process Control Data Historian Systems.

...With GPU acceleration via CUDA and OpenCV integration, it achieves high performance in image recognition tasks. Its simplicity, combined with powerful capabilities, has made Darknet one of the most influential projects in the computer vision community.

The Twitter Image Pipeline is a streamlined framework for fetching and storing images in an application. The high-level concept is that all requests to fetch or store an image go through an image pipeline which encapsulates the work of checking the in-memory caches and an on disk cache before retrieving the image from over the network as well as keeping the caches both up to date and pruned.

SAFS is a software test automation framework supporting data-driven (aka keyword-driven) functional test automation and associated services. The framework can run stand-alone on Windows, Linux, and Mac as well as integrate the use of IBM Rational Functional Tester, IBM Rational Robot, Smart Bear/AutomatedQA Test Complete, Apple XCode UIAutomation, Android SDK Automaton, Thoughtworks Selenium, and several other tools.

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.

...Easy and fast. Tesseract OCR iOS and TesseractOCR.framework are distributed under the MIT license. These are the current versions of the upstream bundled libraries within the framework that this repository provides, Tesseract 3.03-rc1, Leptonica 1.72, Image libraries, Libtiff 4.0.4, Libpng 1.6.18, and Libjpeg 9a.

HIPAcc development has moved to github: https://github.com/hipacc HIPAcc allows to design image processing kernels and algorithms in a domain-specific language (DSL). From this high-level description, low-level target code for GPU accelerators is generated using source-to-source translation. As back ends, the framework supports CUDA, OpenCL, and Renderscript. HIPAcc allows programmers to develop imaging applications while providing high productivity, flexibility and portability as well as competitive performance: the same algorithm description serves as basis for targeting different GPU accelerators and low-level languages.

Heimdall is a sensor fusion framework. It uses a component-based approach to create a sensor fusion middleware. This is the core component, which controls the interaction between the components used to do the sensing and the processing of data.

Framework to simplify developing applications that use wireless body sensor networks (bodynets). Manages sensor sampling, data buffering, local processing and communication. Supports embedded devices running TinyOS and any Java-capable gateway.