YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/

Go package for computer vision using OpenCV 4 and beyond. Includes support for DNN, CUDA, and OpenCV Contrib.

OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference

NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥

TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and …

Pre-trained Deep Learning models and demos (high quality and extremely fast)

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.

An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

⚡️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.

OpenMMLab Model Deployment Framework

Fast and accurate human pose estimation in PyTorch. Contains implementation of "Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose" paper.

Awesome OCR multiple programing languages toolkits based on ONNXRuntime, OpenVION and PaddlePaddle.

📚 Jupyter notebook tutorials for OpenVINO™

Deep learning gateway on Raspberry Pi and other edge devices

Add bisenetv2. My implementation of BiSeNet

Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™

Contains examples for the Movidius Neural Compute Stick.

Fast stable diffusion on CPU

Fast and accurate face landmark detection library using PyTorch; Support 68-point semi-frontal and 39-point profile landmark detection; Support both coordinate-based and heatmap-based inference; Up to 100 FPS landmark inference speed with SOTA face detector on CPU.

Neural Network Compression Framework for enhanced OpenVINO™ inference