There are 46 repositories under onnx topic.
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
Visualizer for neural network, deep learning and machine learning models
ncnn is a high-performance neural network inference framework optimized for the mobile platform
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.
Open source real-time translation app for Android that runs locally
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
Remove backgrounds from images directly in the browser environment with ease and no additional costs or privacy concerns. Explore an interactive demo.
Deep Learning Visualization Toolkit(『飞桨』深度学习可视化工具 )
Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple
PyTorch ,ONNX and TensorRT implementation of YOLOv4
Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://intellabs.github.io/distiller
Java version of LangChain
DAMO-YOLO: a fast and accurate object detection method with some new techs, including NAS backbones, efficient RepGFPN, ZeroHead, AlignedOTA, and distillation enhancement.
🛠 A lite C++ toolkit of awesome AI models, support ONNXRuntime, MNN. Contains YOLOv5, YOLOv6, YOLOX, YOLOv8, FaceDet, HeadSeg, HeadPose, Matting etc. Engine: ONNXRuntime, MNN.
Silero VAD: pre-trained enterprise-grade Voice Activity Detector
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.
Effortless data labeling with AI support from Segment Anything and other awesome models.
🔥🔥🔥🔥 (Earlier YOLOv7 not official one) YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥
Sparsity-aware deep learning inference runtime for CPUs
The official PyTorch implementation of Towards Fast, Accurate and Stable 3D Dense Face Alignment, ECCV 2020.
⚡️An Easy-to-use and Fast Deep Learning Model Deployment Toolkit for ☁️Cloud 📱Mobile and 📹Edge. Including Image, Video, Text and Audio 20+ main stream scenarios and 150+ SOTA models with end-to-end optimization, multi-platform and multi-framework support.
An OBS plugin for removing background in portrait images (video), making it easy to replace the background when recording or streaming.
OpenMMLab Model Deployment Framework
Speech-to-text, text-to-speech, and speaker recognition using next-gen Kaldi with onnxruntime without Internet connection. Support embedded systems, Android, iOS, Raspberry Pi, RISC-V, x86_64 servers, websocket server/client, C/C++, Python, Kotlin, C#, Go, NodeJS, Java, Swift, Dart, JavaScript, Flutter
🚀 Accelerate training and inference of 🤗 Transformers and 🤗 Diffusers with easy to use hardware optimization tools
Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms