yolor

implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)

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

NVIDIA DeepStream SDK 6.1 / 6.0.1 / 6.0 configuration for YOLO models

Support Yolov5(4.0)/Yolov5(5.0)/YoloR/YoloX/Yolov4/Yolov3/CenterNet/CenterFace/RetinaFace/Classify/Unet. use darknet/libtorch/pytorch/mxnet to onnx to tensorrt

🔥🔥🔥 YOLOR 训练自己的数据集，详细教程

使用ONNXRuntime部署anchor-free系列的YOLOR，包含C++和Python两种版本的程序

🚀 ⭐ The list of the most popular YOLO algorithms - awesome YOLO

Demos for how to use the shared libs of Lite.AI.ToolKit🚀🚀🌟. (https://github.com/DefTruth/lite.ai.toolkit)

Real Time Lane Detection + Lane Line Generation + Object Detection + Object Counting (DeepSort, YoloR)

Experimental implementation of real-time object detection algorithm YOLOR on embedded systems (edge computing devices)

Final project of VRDL course in 2021 fall semester at NYCU.

FSOD stands for Firearms and Sharp Object Detector. In conclusion, this dashboard is a web application made with streamlit that can detect several kind of firearms and sharp object threat. Object detection algorithm used to make the model are YOLO-R and also used Deepsort for tracking purpose.

🤖 Trained YOLOR model to detect texts on manga pages.

fire detection with yoloR