Easy and fast 2d human and animal multi pose estimation using SOTA ViTPose [Y. Xu et al., 2022] Real-time performances and multiple skeletons supported.

The project is an official implement of our ECCV2018 paper "Simple Baselines for Human Pose Estimation and Tracking(https://arxiv.org/abs/1804.06208)"

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

Real-time pose estimation accelerated with NVIDIA TensorRT

A PyTorch port of Google Movenet (inference only)

A Pytorch implementation of MoveNet from Google. Include training code and pre-trained model.

Code release for CVPR'24 submission 'OmniGlue'

OCR, layout analysis, reading order, table recognition in 90+ languages

code for CVPR2024 paper: DiffMOT: A Real-time Diffusion-based Multiple Object Tracker with Non-linear Prediction

Implementation of XFeat (CVPR 2024). Do you need robust and fast local feature extraction? You are in the right place!

[ECCV2024] API code for T-Rex2: Towards Generic Object Detection via Text-Visual Prompt Synergy

LLM training in simple, raw C/CUDA

Code for "Efficient LoFTR: Semi-Dense Local Feature Matching with Sparse-Like Speed", CVPR 2024

[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation

MegEngine implementation of YOLOX

Arduino hardware package for ATmega8, ATmega48, ATmega88, ATmega168, ATmega328 and ATmega328PB

An implementation of global matting algorithm for OpenCV.

M. Beyeler (2015). OpenCV with Python Blueprints: Design and develop advanced computer vision projects using OpenCV with Python, Packt Publishing Ltd., ISBN 978-178528269-0.

Mirror of AVA raspicam source code http://www.uco.es/investiga/grupos/ava/node/40

Learn OpenCV : C++ and Python Examples

Program for testing the KAZE and A-KAZE ports in OpenCV. The idea is to test the OpenCV port to match the performance of the original library.

A local descriptor named MROGH, published in "Aggregating Gradient Distributions into Intensity Orders: A Novel Local Image Descriptor, CVPR 2011"