🔥🔥🔥 专注于YOLO11，YOLOv8、TYOLOv12、YOLOv10、RT-DETR、YOLOv7、YOLOv5改进模型，Support to improve backbone, neck, head, loss, IoU, NMS and other modules🚀

Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!

Python implementation of the IOU Tracker

Provides easy-to-use async IO interface with io_uring

k-means clustering with the Intersection over Union (IoU) metric as described in the YOLO9000 paper

A Wrapper for socket.io-client-csharp to work with Unity.

ncnn example: mask detection: anticonv face detection: retinaface&&mtcnn&&centerface, track: iou tracking, landmark: zqcnn, recognize: mobilefacenet classifier: mobilenet object detecter: mobilenetssd

Delightful io_uring packages and resources

Differentiable IoU of rotated bounding boxes using Pytorch

CIA-SSD: Confident IoU-Aware Single Stage Object Detector From Point Cloud, AAAI 2021.

VarifocalNet: An IoU-aware Dense Object Detector

Rust interface to io_uring

Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression (AAAI 2020)

🔥🔥🔥 专注于YOLO改进模型，Support to improve backbone, neck, head, loss, IoU, NMS and other modules🚀

Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression (AAAI 2020)

遥感图像的语义分割，基于深度学习，在Tensorflow框架下，利用TF.Keras，运行环境TF2.0+

Distance-IoU Loss into YOLO v3

The expense sharing app.

A PyTorch implementation of the paper `Probabilistic Anchor Assignment with IoU Prediction for Object Detection` ECCV 2020 (https://arxiv.org/abs/2007.08103)

Boundary IoU API (Beta version)

☁️💡🎈专注于改进YOLOv7，Support to improve Backbone, Neck, Head, Loss, IoU, NMS and other modules

io_uring support for go

Fix broken USB HID descriptors. Now with Noppoo Choc Mini support!

YOLOv8检测模块组合优化改进（成功涨点）:添加GAM注意力机制；添加小目标检测头；替换为Wise_IoU损失函数+完整web端展示(实现简单目标跟踪功能)

The brief implementation and using examples of object detection usages like, IoU, NMS, soft-NMS, SmoothL1、IoU loss、GIoU loss、 DIoU loss、CIoU loss, cross-entropy、focal-loss、GHM, AP/MAP and so on by Pytorch.

[CVPR 2021] PyTorch implementation of 3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection.

Location-Sensitive Visual Recognition with Cross-IOU Loss

[NeurIPS 2021] Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression

Machine learning approach of automatic identification and counting of blood cells (RBC, WBC, and Platelet) with KNN and IOU based verification.

"Rethinking IoU-based Optimization for Single-stage 3D Object Detection", ECCV2022 accept!