Nuzhny007

Multitarget-tracker

Hungarian algorithm + Kalman filter multitarget (multi-object) tracker implementation.

yolo-tensorrt

TensorRT8.Support Yolov5n,s,m,l,x .darknet -> tensorrt. Yolov4 Yolov3 use raw darknet *.weights and *.cfg fils. If the wrapper is useful to you,please Star it.

dehaze

Algorithm for dehazing image

trt_yolo_video_pipeline

TensorRT+YOLO系列的 多路 多卡 多实例 并行视频分析处理案例

abandoned_objects

ApraPipes

A pipeline framework for developing video and image processing application. Supports multiple GPUs and Machine Learning tooklits

cacaMap

a c++ Qt based map widget

Cal_PnP

C++ implementation of semi-automatic camera calibration based on Perspective-n-Point (PnP)

clip.cpp

CLIP inference in plain C/C++ with no extra dependencies

CSVA

dl_model_infer

EmulatorMake

geographiclib

Main repository for GeographicLib

GRAL

Gral calculation core

GRAMM

Gramm calculation core

gstreamer-cpp-example

gstreamer-rtsp-ssl-example

Gstreamer RTSP SSL example

GUI

Graphical User Interface for the atmospheric dispersion model GRAL and the mesoscale wind field model GRAMM

mv-extractor

Extract frames and motion vectors from H.264 and MPEG-4 encoded video.

opencv

Open Source Computer Vision Library

opencv_contrib

Repository for OpenCV's extra modules

rk3588-yolo-demo

The project is a multi-threaded inference demo of Yolov8 running on the RK3588 platform, which has been adapted for reading video files and camera feeds. The demo uses the Yolov8n model for file inference, with a maximum inference frame rate of up to 100 frames per second.

RuCLIP

Unofficial c++ LibTorch implementation of RuCLIP (Sber AI)

segment-anything-cpp-wrapper

simsimd

SIMD-accelerated similarity measures, metrics, distance functions for x86 and Arm: AVX2, AVX512, NEON, SVE

tensorrt-yolov6

C++ implementation of YOLOv6 using TensorRT

Yolo-LibTorch

一个 LibTorch 版本的 Yolo 封装库

yolo_deepstream

yolo model qat and deploy with deepstream&tensorrt

Yolov5-instance-seg-tensorrt

fish-kong/Yolov5-Instance-Seg-Tensorrt-CPP

yolov7

Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors