implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
翻译 - 论文的实施-您只能学习一种表示形式：用于多个任务的统一网络（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
Implementation for the paper 'YOLO-ReT: Towards High Accuracy Real-time Object Detection on Edge GPUs'
使用ONNXRuntime部署anchor-free系列的YOLOR，包含C++和Python两种版本的程序
🔥🔥🔥 YOLOR 训练自己的数据集，详细教程
Yolor and DeepSort
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
fire detection with yoloR
🛠 A lite C++ toolkit of 100+ awesome AI models, support ONNXRuntime, MNN, NCNN, TNN and TensorRT. 🎉🎉
翻译 - 🍅🍅A lite C++ 工具包，包含具有 ONNXRuntime、NCNN、MNN 和 TNN 的出色 AI 模型。 YOLOX、YOLOP、YOLOv5、YOLOR、NanoDet、YOLOX、SCRFD、YOLOX。 MNN、NCNN、TNN、ONNXRuntime、CPU/GPU。
🔥🔥🔥 专注于YOLOv5，YOLOv7、YOLOv8、YOLOv9改进模型，Support to improve backbone, neck, head, loss, IoU, NMS and other modules🚀
Deepsort with yolo series. This project support the existing yolo detection model algorithm (YOLOV8, YOLOV7, YOLOV6, YOLOV5, YOLOV4Scaled, YOLOV4, YOLOv3', PPYOLOE, YOLOR, YOLOX ).
Keras beit,caformer,CMT,CoAtNet,convnext,davit,dino,efficientdet,edgenext,efficientformer,efficientnet,eva,fasternet,fastervit,fastvit,flexivit,gcvit,ghostnet,gpvit,hornet,hiera,iformer,inceptionnext,...