Popular GitHub Repositories for Onnx Runtime

Silero VAD: pre-trained enterprise-grade Voice Activity Detector

YoloDotNet - A C# .NET 8.0 project for Classification, Object Detection, OBB Detection, Segmentation and Pose Estimation in both images and videos.

? Use YOLO11 in real-time for object detection tasks, with edge performance ?? powered by ONNX-Runtime.

Edge Inference in Browser with Transformer NLP model

Rust wrapper for Microsoft's ONNX Runtime (version 1.8)

The Triton backend for the ONNX Runtime.

A curated list of awesome inference deployment framework of artificial intelligence (AI) models. OpenVINO, TensorRT, MediaPipe, TensorFlow Lite, TensorFlow Serving, ONNX Runtime, LibTorch, NCNN, TNN, MNN, TVM, MACE, Paddle Lite, MegEngine Lite, OpenPPL, Bolt, ExecuTorch.

Base on tensorrt version 8.2.4, compare inference speed for different tensorrt api.

SOTA image super-resolution in JavaScript/Wasm using an ONNX-ported SwinIR model

Deep Learning Inference benchmark. Supports OpenVINO? toolkit, TensorFlow, TensorFlow Lite, ONNX Runtime, OpenCV DNN, MXNet, PyTorch, Apache TVM, ncnn, PaddlePaddle, etc.

基于 ResNet 的花卉分类识别系统。A ResNet-based flower classification and recognition system.

Easy-to-use danbooru anime image classification model

Renesas RZ/G AI BSP

Comparing PyTorch, JIT and ONNX for inference with Transformers

Babylon.cpp is a C and C++ library for grapheme to phoneme conversion and text to speech synthesis. For phonemization a ONNX runtime port of the DeepPhonemizer model is used. For speech synthesis VITS models are used. Piper models are compatible after a conversion script is run.

Machine learning for code reviews!

Enterprise VAD (Voice Activity Detection) in C#.NET (.NET 9.0) with Microsoft.ML.Net, ONNXRuntime and DirectML. The easiest, efficient, and performant Silero VAD implementation! Always open for PRs.

Voice100 Android App is a TTS/ASR sample app that uses ONNX Runtime and Voice100 neural TTS/ASR models on Xamarin. Inference of Voice100 is low cost as its models are tiny and only depend on CNN without recursion.

This project includes implementations of YOLOv8, RT-DETR-V2(RTDETR), MobileSAM, and NanoSAM on TensorRT, ONNX Runtime, and RKNN, along with support for asynchronous inference workflows. It provides a user-friendly deep learning deployment tool for seamless algorithm migration across different inference frameworks.

Run ONNX machine learning models on AWS Lambda