📚 Jupyter notebook tutorials for OpenVINO™
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Updated
May 29, 2024 - Jupyter Notebook
📚 Jupyter notebook tutorials for OpenVINO™
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
This repository is a home to Intel® Deep Learning Streamer (Intel® DL Streamer) Pipeline Framework. Pipeline Framework is a streaming media analytics framework, based on GStreamer* multimedia framework, for creating complex media analytics pipelines.
A scalable inference server for models optimized with OpenVINO™
🤗 Optimum Intel: Accelerate inference with Intel optimization tools
image editor with AI models written in C++, running on CPU
A unified multi-backend utility for benchmarking Transformers, Timm, PEFT, Diffusers and Sentence-Transformers with full support of Optimum's hardware optimizations & quantization schemes.
Software Development Kit (SDK) for the Intel® Geti™ platform for Computer Vision AI model training.
Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™
Awesome OCR multiple programing languages toolkits based on ONNXRuntime, OpenVION and PaddlePaddle.
Implementing YOLOv10 object detection using OpenVINO for efficient and accurate real-time inference.
Neural Network Compression Framework for enhanced OpenVINO™ inference
OpenVINO operator for OpenShift and Kubernetes
Efficient CPU/GPU/Vulkan ML Runtimes for VapourSynth (with built-in support for waifu2x, DPIR, RealESRGANv2/v3, Real-CUGAN, RIFE, SCUNet and more!)
A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.
Repository for OpenVINO's extra modules
Fast stable diffusion on CPU
nndeploy是一款模型端到端部署框架。以多端推理以及基于有向无环图模型部署为基础,致力为用户提供跨平台、简单易用、高性能的模型部署体验。
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