Search Results for "weight scale software"
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Showing 19 open source projects for "weight scale software"
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Selenium
Browser automation framework and ecosystem
Selenium automates browsers. That's it! What you do with that power is entirely up to you. Primarily it is for automating web applications for testing purposes, but is certainly not limited to just that. Boring web-based administration tasks can (and should) also be automated as well. If you want to create robust, browser-based regression automation suites and tests, scale and distribute scripts across many environments, then you want to use Selenium WebDriver, a collection of language... -
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userver
Production-ready C++ Asynchronous Framework with rich functionality
userver is a modern C++ framework for building asynchronous, high-performance microservices. Developed by Yandex, it provides a robust architecture for writing non-blocking network applications, with built-in support for gRPC, HTTP, database clients, metrics, and more. userver is designed for production-scale backend systems that require low latency and high reliability. -
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Vespa
The open big data serving engine
Make AI-driven decisions using your data, in real-time. At any scale, with unbeatable performance. Vespa is a full-featured text search engine and supports both regular text search and fast approximate vector search (ANN). This makes it easy to create high-performing search applications at any scale, whether you want to use traditional techniques or a modern vector-based approach. You can even combine both approaches efficiently in the same query, something no other engine can do.... -
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bitnet.cpp
Official inference framework for 1-bit LLMs
bitnet.cpp is the official open-source inference framework and ecosystem designed to enable ultra-efficient execution of 1-bit large language models (LLMs), which quantize most model parameters to ternary values (-1, 0, +1) while maintaining competitive performance with full-precision counterparts. At its core is bitnet.cpp, a highly optimized C++ backend that supports fast, low-memory inference on both CPUs and GPUs, enabling models such as BitNet b1.58 to run without requiring enormous... -
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OneFlow
OneFlow is a deep learning framework designed to be user-friendly
OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient. An extension for OneFlow to target third-party compiler, such as XLA, TensorRT and OpenVINO etc.CUDA runtime is statically linked into OneFlow. OneFlow will work on a minimum supported driver, and any driver beyond. For more information. Distributed performance (efficiency) is the core technical difficulty of the deep learning framework. OneFlow focuses on performance improvement and heterogeneous... -
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Apache Weex
A framework for building Mobile cross-platform UI
Weex is a framework for building performant mobile apps with modern web technology. Weex is using native components and native modules to take advantage of native rendering performance and platform capabilities. Both components and modules are pluggable and extendable. You can use a single codebase to generate different bundle files to running on both Webs, Android and iOS platforms. Native components and modules have a different implementation on each platform, but they all exposed the same... -
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RefineNet
RefineNet: Multi-Path Refinement Networks
...It provides trained models for datasets such as PASCAL VOC 2012, Cityscapes, NYUDv2, Person_Parts, PASCAL_Context, SUNRGBD, and ADE20k, with versions based on ResNet-101 and ResNet-152 backbones. The repository supports both single-scale and multi-scale prediction, with scripts for training, testing, and evaluating segmentation performance. While this codebase is specific to MATLAB and MatConvNet, a PyTorch implementation and lighter-weight variants are also available from the community. -
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Caffe Framework
Caffe, a fast open framework for deep learning
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license. Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine... -
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Caffe
A fast open framework for deep learning
Caffe is an open source deep learning framework that’s focused on expression, speed and modularity. It’s got an expressive architecture that encourages application and innovation, and extensible code that’s great for active development. Caffe also offers great speed, capable of processing over 60M images per day with a single NVIDIA K40 GPU. It’s arguably one of the fastest convnet implementations around. Caffe is developed by the Berkeley AI Research (BAIR)/The Berkeley Vision and... -
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ProTest
A minimalistic test framework written in C++.
A minimalistic test framework written in C++ providing scenario based, stateful acceptance testing where application user interface is mocked using test stubs. Refer to Sample.cpp for usage guidance. The sample defines a simple application class, fake user interface implementing the same abstract interface as the application requires, a test context to hold test state and pass it on among steps, and a few test steps. It then adds all the test steps to a test scenario. Then the default() main... -
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Project provides light-weight, cross-platform library with utility classes that could be used by c++-based projects.
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A parallel-programming framework for concurrently running large numbers of small autonomous jobs, or microthreads, across multiple cores in a CPU or CPUs in a cluster. Each microthread is conceptually similar to a task in Ada and it is much lighter weight than an operating system thread. SpikeOS was designed to handle millions of microthreads, for example in a neural network hosting millions of spiking model neurons. SpikeOS handles microthread scheduling, synchronization, distribution...
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This is an actor-based framework for C++. Actors are light-weight objects, and they interact fully asynchronously with messages. It’s intended for multi-core processors only and doesn’t have any network routines.
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component is a cross-platform C++ library for building light-weight component architectures. It provides a convenient way for creating program design using dependency injection container. library is based on the high-quality Boost source libraries.
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The Open Reflective Component Architecture , ORCAN, is designed to build the basis for a rapid incorporation of existing software packages into large-scale software projects Project is dead, however - please feel free to check and reuse code!
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A light-weight cross platform C++ library for console and file I/O, fast data structures and algorithms, CPU identification (CPUID), and sockets (TCP and UDP).
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Chomoko is a simple, light-weight, intuitive message transferring library. Pure C++ (with sockets), Open Source (GPL), Performance-Oriented, Assured (Reliable), Once Delivery, Point-to-Point, Easy to Setup and Use, Simple, and Clean
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it is a light-weight portable c++ class library include threadpool, socket, dynamic class loadding , server, httpserver/servlets, etc. it is a practical utility for who do not want to learn the complex Boost/ACE.
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AspectCOM intends to bring AOP into component-based development, specifically, Microsoft Component Object Model (COM). It is fast, light-weight and can be easily integrated with existing COM components.
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