Search Results for "openvino"
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Showing 24 open source projects for "openvino"
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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. -
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OpenVINO Notebooks
Jupyter notebook tutorials for OpenVINO
...The tutorials also illustrate how OpenVINO integrates with models from frameworks like PyTorch, TensorFlow, and ONNX to accelerate inference workloads. Many notebooks include end-to-end examples that show how to prepare input data, load optimized models, run inference, and visualize results. The project is particularly useful for developers who want to learn how to optimize machine learning inference pipelines for production environments. -
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OpenVINO AI Plugins for Audacity
A set of AI-enabled effects, generators, and analyzers for Audacity
A set of AI-enabled effects, generators, and analyzers for Audacity. These AI features run 100% locally on your PC, no internet connection is necessary. OpenVINO™ is used to run AI models on supported accelerators found on the user's system such as CPU, GPU, and NPU. -
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OpenVINO Model Server
A scalable inference server for models optimized with OpenVINO
OpenVINO™ Model Server is a high-performance inference serving system designed to host and serve machine learning models that have been optimized with the OpenVINO toolkit. It’s implemented in C++ for scalability and efficiency, making it suitable for both edge and cloud deployments where inference workloads must be reliable and high throughput. -
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OpenVINO Training Extensions
Trainable models and NN optimization tools
...NNCF optimization used for trained snapshots in a framework-specific format. POT optimization used for models exported in the OpenVINO IR format. -
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FastSD CPU
Fast stable diffusion on CPU and AI PC
...The repository contains multiple interfaces including a desktop GUI for simple generation, an advanced web-based UI with support for extensions like LoRA and ControlNet, and a command-line interface for scripted usage or server deployments. With support for performance-oriented libraries such as OpenVINO and hardware acceleration on platforms like Intel AI PCs, FastSD CPU aims to shrink generation times dramatically compared with naive CPU implementations. -
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Open Model Zoo
Pre-trained Deep Learning models and demos
Open Model Zoo is a large repository of high-quality pre-trained deep learning models and demonstration applications designed to work with the OpenVINO™ toolkit, offering a comprehensive starting point for a wide range of AI and computer vision workloads. It includes hundreds of models covering object detection, classification, segmentation, pose estimation, speech recognition, text-to-speech, and more, many of which are already converted into formats optimized for inference on CPUs, GPUs, VPUs, and other accelerators supported by OpenVINO. -
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NNCF
Neural Network Compression Framework for enhanced OpenVINO
NNCF (Neural Network Compression Framework) is an optimization toolkit for deep learning models, designed to apply quantization, pruning, and other techniques to improve inference efficiency. -
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Anomalib
An anomaly detection library comprising state-of-the-art algorithms
...Its design supports unsupervised or semi-supervised paradigms, making it especially powerful for scenarios where only “normal” data is readily available and defects must be detected without exhaustive labeling. Combined with its CLI and integration with optimization tools like OpenVINO, it’s suitable for both research and edge deployment tasks. -
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WhisperLive
A nearly-live implementation of OpenAI's Whisper
...It runs as a server–client system in which the server hosts a Whisper backend and clients stream audio to be transcribed with very low delay. The project supports multiple inference backends, including Faster-Whisper, NVIDIA TensorRT, and OpenVINO, allowing you to target GPUs and different CPU architectures efficiently. It can handle microphone input, pre-recorded audio files, and network streams such as RTSP and HLS, making it flexible for live events, monitoring, or accessibility workflows. Configuration options let you control the number of clients, maximum connection time, and threading behavior so the server can be tuned for different deployment environments. ... -
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ChatGLM3
ChatGLM3 series: Open Bilingual Chat LLMs | Open Source Bilingual Chat
...The repo ships Python APIs, CLI and web demos (Gradio/Streamlit), an OpenAI-format API server, and a compact fine-tuning kit. Quantization (4/8-bit), CPU/MPS support, and accelerator backends (TensorRT-LLM, OpenVINO, chatglm.cpp) enable lightweight local or edge deployment. -
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Netron
Visualizer for neural network, deep learning, machine learning models
...Netron supports ONNX, Keras, TensorFlow Lite, Caffe, Darknet, Core ML, MNN, MXNet, ncnn, PaddlePaddle, Caffe2, Barracuda, Tengine, TNN, RKNN, MindSpore Lite, and UFF. Netron has experimental support for TensorFlow, PyTorch, TorchScript, OpenVINO, Torch, Arm NN, BigDL, Chainer, CNTK, Deeplearning4j, MediaPipe, ML.NET, scikit-learn, TensorFlow.js. There is an extense variety of sample model files to download or open using the browser version. It is supported by macOS, Windows, Linux, Python Server and browser. -
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Rapid LaTeX OCR
Formula recognition based on LaTeX-OCR and ONNXRuntime
...The reasoning code in the repo is modified from LaTeX-OCR, the model has all been converted to ONNX format, and the reasoning code has been simplified, Inference is faster and easier to deploy. The repo only has codes based on ONNXRuntime or OpenVINO inference in onnx format and does not contain training model codes. If you want to train your own model, please move to LaTeX-OCR. When installing the package through pip, the model file will be automatically downloaded and placed under models in the installation directory. -
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llmware
Unified framework for building enterprise RAG pipelines
...One of the framework’s defining characteristics is its collection of small specialized language models optimized for specific tasks such as summarization, classification, and document analysis. The system supports a wide range of inference backends including PyTorch, OpenVINO, ONNX Runtime, and other optimized runtimes, allowing developers to choose the most efficient execution environment for their hardware. -
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Spark NLP
State of the Art Natural Language Processing
Experience the power of large language models like never before, unleashing the full potential of Natural Language Processing (NLP) with Spark NLP, the open source library that delivers scalable LLMs. The full code base is open under the Apache 2.0 license, including pre-trained models and pipelines. The only NLP library built natively on Apache Spark. The most widely used NLP library in the enterprise. Spark ML provides a set of machine learning applications that can be built using two main... -
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GoCV
Go package for computer vision using OpenCV 4 and beyond
GoCV gives programmers who use the Go programming language access to the OpenCV 4 computer vision library. The GoCV package supports the latest releases of Go and OpenCV v4.5.4 on Linux, macOS, and Windows. Our mission is to make the Go language a “first-class” client compatible with the latest developments in the OpenCV ecosystem. Computer Vision (CV) is the ability of computers to process visual information, and perform tasks normally associated with those performed by humans. CV software... -
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Triton Inference Server
The Triton Inference Server provides an optimized cloud
Triton Inference Server is an open-source inference serving software that streamlines AI inferencing. Triton enables teams to deploy any AI model from multiple deep learning and machine learning frameworks, including TensorRT, TensorFlow, PyTorch, ONNX, OpenVINO, Python, RAPIDS FIL, and more. Triton supports inference across cloud, data center, edge, and embedded devices on NVIDIA GPUs, x86 and ARM CPU, or AWS Inferentia. Triton delivers optimized performance for many query types, including real-time, batched, ensembles, and audio/video streaming. Provides Backend API that allows adding custom backends and pre/post-processing operations. ... -
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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 distributed expansion. ... -
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+Ubuntu 24.04 WMJ Robotics
Ubuntu Release for WMJ Robomaster Team Vision Group
Ubuntu release contains: ros2, ceres-solver, onnxruntime, openvino, zsh and etc. for basic use, edit, and compile for team code. -
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pipeless
A computer vision framework to create and deploy apps in minutes
Pipeless is an open-source computer vision framework to create and deploy applications without the complexity of building and maintaining multimedia pipelines. It ships everything you need to create and deploy efficient computer vision applications that work in real-time in just minutes. Pipeless is inspired by modern serverless technologies. It provides the development experience of serverless frameworks applied to computer vision. You provide some functions that are executed for new... -
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NanoDet-Plus
Lightweight anchor-free object detection model
...We also introduce a light feature pyramid called Ghost-PAN to enhance multi-layer feature fusion. These improvements boost previous NanoDet's detection accuracy by 7 mAP on COCO dataset. NanoDet provide multi-backend C++ demo including ncnn, OpenVINO and MNN. There is also an Android demo based on ncnn library. Supports various backends including ncnn, MNN and OpenVINO. Also provide Android demo based on ncnn inference framework. -
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YOLOX
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. YOLOX is an anchor-free version of YOLO, with a simpler design but better performance! It aims to bridge the gap between research and industrial communities. Prepare your own dataset with images and labels first. For labeling images, you can use tools like Labelme or CVAT. One more thing worth noting is that you should also implement pull_item and load_anno method for the Mosiac and MixUp augmentations. ... -
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nGraph
nGraph has moved to OpenVINO
Frameworks using nGraph Compiler stack to execute workloads have shown up to 45X performance boost when compared to native framework implementations. We've also seen performance boosts running workloads that are not included on the list of Validated workloads, thanks to nGraph's powerful subgraph pattern matching. Additionally, we have integrated nGraph with PlaidML to provide deep learning performance acceleration on Intel, nVidia, & AMD GPUs. nGraph Compiler aims to accelerate developing... -
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openvino-aicra
because... we need a deb
The openvino toolkit is an open source project so I just took the files and rolled these into a deb. I haven't even tested this yet. Use at your own risk. Anyway, should work fine. I hope ;) - update: Not ...exactly... Need to make sure the contents go in the right place. Other than that, if you want the files - cool but not cool writing to / First roll up...
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