Search Results for "c-sharp"
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Showing 305 open source projects for "c-sharp"
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PyTorch
Open source machine learning framework
PyTorch is a Python package that offers Tensor computation (like NumPy) with strong GPU acceleration and deep neural networks built on tape-based autograd system. This project allows for fast, flexible experimentation and efficient production. PyTorch consists of torch (Tensor library), torch.autograd (tape-based automatic differentiation library), torch.jit (a compilation stack [TorchScript]), torch.nn (neural networks library), torch.multiprocessing (Python multiprocessing), and... -
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AlphaZero.jl
A generic, simple and fast implementation of Deepmind's AlphaZero
Beyond its much publicized success in attaining superhuman level at games such as Chess and Go, DeepMind's AlphaZero algorithm illustrates a more general methodology of combining learning and search to explore large combinatorial spaces effectively. We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C... -
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Vosk Speech Recognition Toolkit
Offline speech recognition API for Android, iOS, Raspberry Pi
..., reconfigurable vocabulary and speaker identification. Speech recognition bindings are implemented for various programming languages like Python, Java, Node.JS, C#, C++, Rust, Go and others. Vosk supplies speech recognition for chatbots, smart home appliances, and virtual assistants. It can also create subtitles for movies, and transcription for lectures and interviews. Vosk scales from small devices like Raspberry Pi or Android smartphones to big clusters. -
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ONNX Runtime
ONNX Runtime: cross-platform, high performance ML inferencing
ONNX Runtime is a cross-platform inference and training machine-learning accelerator. ONNX Runtime inference can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators... -
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TensorFlow
TensorFlow is an open source library for machine learning
Originally developed by Google for internal use, TensorFlow is an open source platform for machine learning. Available across all common operating systems (desktop, server and mobile), TensorFlow provides stable APIs for Python and C as well as APIs that are not guaranteed to be backwards compatible or are 3rd party for a variety of other languages. The platform can be easily deployed on multiple CPUs, GPUs and Google's proprietary chip, the tensor processing unit (TPU). TensorFlow... -
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emgucv
Cross platform .Net wrapper to the OpenCV image processing library
Emgu CV is a cross platform .Net wrapper to the OpenCV image processing library. Allowing OpenCV functions to be called from .NET compatible languages. The wrapper can be compiled by Visual Studio and Unity, it can run on Windows, Linux, Mac OS, iOS and Android. -
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OpenVINO
OpenVINO™ Toolkit repository
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference. Boost deep learning performance in computer vision, automatic speech recognition, natural language processing and other common tasks. Use models trained with popular frameworks like TensorFlow, PyTorch and more. Reduce resource demands and efficiently deploy on a range of Intel® platforms from edge to cloud. This open-source version includes several components: namely Model Optimizer, OpenVINO™ Runtime,... -
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libvips
A fast image processing library with low memory needs
... of image formats, including JPEG, JPEG2000, JPEG-XL, TIFF, PNG, WebP, HEIC, AVIF, FITS, Matlab, OpenEXR, PDF, SVG, HDR, PPM / PGM / PFM, CSV, GIF, Analyze, NIfTI, DeepZoom, and OpenSlide. It can also load images via ImageMagick or GraphicsMagick, letting it work with formats like DICOM. It comes with bindings for C, C++, and the command-line. Full bindings are available for Ruby, Python, PHP, C# / .NET, Go, and Lua. -
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TensorRT
C++ library for high performance inference on NVIDIA GPUs
NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference. It includes a deep learning inference optimizer and runtime that delivers low latency and high throughput for deep learning inference applications. TensorRT-based applications perform up to 40X faster than CPU-only platforms during inference. With TensorRT, you can optimize neural network models trained in all major frameworks, calibrate for lower precision with high accuracy, and deploy to hyperscale data centers,... -
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The Julia Programming Language
High-level, high-performance dynamic language for technical computing
.... Libraries from Python, R, C/Fortran, C++, and Java can also be used. -
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Compute Library
The Compute Library is a set of computer vision and machine learning
The Compute Library is a set of computer vision and machine learning functions optimized for both Arm CPUs and GPUs using SIMD technologies. The library provides superior performance to other open-source alternatives and immediate support for new Arm® technologies e.g. SVE2. -
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ONNX
Open standard for machine learning interoperability
ONNX is an open format built to represent machine learning models. ONNX defines a common set of operators - the building blocks of machine learning and deep learning models - and a common file format to enable AI developers to use models with a variety of frameworks, tools, runtimes, and compilers. Open Neural Network Exchange (ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models, both... -
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dlib
Toolkit for making machine learning and data analysis applications
Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is about... -
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Tiny CUDA Neural Networks
Lightning fast C++/CUDA neural network framework
This is a small, self-contained framework for training and querying neural networks. Most notably, it contains a lightning-fast "fully fused" multi-layer perceptron (technical paper), a versatile multiresolution hash encoding (technical paper), as well as support for various other input encodings, losses, and optimizers. We provide a sample application where an image function (x,y) -> (R,G,B) is learned. The fully fused MLP component of this framework requires a very large amount of shared... -
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Torch-TensorRT
PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT
Torch-TensorRT is a compiler for PyTorch/TorchScript, targeting NVIDIA GPUs via NVIDIA’s TensorRT Deep Learning Optimizer and Runtime. Unlike PyTorch’s Just-In-Time (JIT) compiler, Torch-TensorRT is an Ahead-of-Time (AOT) compiler, meaning that before you deploy your TorchScript code, you go through an explicit compile step to convert a standard TorchScript program into a module targeting a TensorRT engine. Torch-TensorRT operates as a PyTorch extension and compiles modules that integrate... -
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ML.NET
Open source and cross-platform machine learning framework for .NET
With ML.NET, you can create custom ML models using C# or F# without having to leave the .NET ecosystem. ML.NET lets you re-use all the knowledge, skills, code, and libraries you already have as a .NET developer so that you can easily integrate machine learning into your web, mobile, desktop, games, and IoT apps. ML.NET offers Model Builder (a simple UI tool) and ML.NET CLI to make it super easy to build custom ML Models. These tools use Automated ML (AutoML), a cutting edge technology... -
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CARLA Simulator
Open-source simulator for autonomous driving research.
CARLA has been developed from the ground up to support development, training, and validation of autonomous driving systems. In addition to open-source code and protocols, CARLA provides open digital assets (urban layouts, buildings, vehicles) that were created for this purpose and can be used freely. The simulation platform supports flexible specification of sensor suites, environmental conditions, full control of all static and dynamic actors, maps generation and much more. Multiple clients... -
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TensorFlow.NET
.NET Standard bindings for Google's TensorFlow for developing models
TensorFlow.NET (TF.NET) provides a .NET Standard binding for TensorFlow. It aims to implement the complete Tensorflow API in C# which allows .NET developers to develop, train and deploy Machine Learning models with the cross-platform .NET Standard framework. TensorFlow.NET has built-in Keras high-level interface and is released as an independent package TensorFlow.Keras. SciSharp STACK's mission is to bring popular data science technology into the .NET world and to provide .NET developers... -
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Triton Inference Server
The Triton Inference Server provides an optimized cloud
... real-time, batched, ensembles, and audio/video streaming. Provides Backend API that allows adding custom backends and pre/post-processing operations. Model pipelines using Ensembling or Business Logic Scripting (BLS). HTTP/REST and GRPC inference protocols based on the community-developed KServe protocol. A C API and Java API allow Triton to link directly into your application for edge and other in-process use cases. -
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mlpack
mlpack: a scalable C++ machine learning library
mlpack is an intuitive, fast, and flexible C++ machine learning library with bindings to other languages. It is meant to be a machine learning analog to LAPACK, and aims to implement a wide array of machine learning methods and functions as a "swiss army knife" for machine learning researchers. In addition to its powerful C++ interface, mlpack also provides command-line programs, Python bindings, Julia bindings, Go bindings and R bindings. Written in C++ and built on the Armadillo linear... -
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ViZDoom
Doom-based AI research platform for reinforcement learning
ViZDoom allows developing AI bots that play Doom using only the visual information (the screen buffer). It is primarily intended for research in machine visual learning, and deep reinforcement learning, in particular. ViZDoom is based on ZDOOM, the most popular modern source-port of DOOM. This means compatibility with a huge range of tools and resources that can be used to create custom scenarios, availability of detailed documentation of the engine and tools and support of Doom community.... -
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SentencePiece
Unsupervised text tokenizer for Neural Network-based text generation
SentencePiece is an unsupervised text tokenizer and detokenizer mainly for Neural Network-based text generation systems where the vocabulary size is predetermined prior to the neural model training. SentencePiece implements subword units (e.g., byte-pair-encoding (BPE) [Sennrich et al.]) and unigram language model [Kudo.]) with the extension of direct training from raw sentences. SentencePiece allows us to make a purely end-to-end system that does not depend on language-specific... -
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Pedalboard
A Python library for audio
pedalboard is a Python library for working with audio: reading, writing, rendering, adding effects, and more. It supports the most popular audio file formats and a number of common audio effects out of the box and also allows the use of VST3® and Audio Unit formats for loading third-party software instruments and effects. pedalboard was built by Spotify’s Audio Intelligence Lab to enable using studio-quality audio effects from within Python and TensorFlow. Internally at Spotify, pedalboard... -
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MegEngine
Easy-to-use deep learning framework with 3 key features
MegEngine is a fast, scalable and easy-to-use deep learning framework with 3 key features. You can represent quantization/dynamic shape/image pre-processing and even derivation in one model. After training, just put everything into your model and inference it on any platform at ease. Speed and precision problems won't bother you anymore due to the same core inside. In training, GPU memory usage could go down to one-third at the cost of only one additional line, which enables the DTR... -
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fastdup
An unsupervised and free tool for image and video dataset analysis
fastdup is a powerful free tool designed to rapidly extract valuable insights from your image & video datasets. Assisting you to increase your dataset images & labels quality and reduce your data operations costs at an unparalleled scale.