iscyy / yoloair2View external linksLinks
☁️💡🎈专注于改进YOLOv7,Support to improve Backbone, Neck, Head, Loss, IoU, NMS and other modules
☆211Apr 22, 2024Updated last year
Alternatives and similar repositories for yoloair2
Users that are interested in yoloair2 are comparing it to the libraries listed below
Sorting:
- 🔥🔥🔥 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 modu…☆2,913Dec 15, 2025Updated 2 months ago
- YOLO Magic🪄 is an extension based on Ultralytics' YOLOv5, designed to provide more powerful functionality and simpler operations for vis…☆513Apr 25, 2024Updated last year
- YOLOv5 Series Multi-backbone(TPH-YOLOv5, Ghostnet, ShuffleNetv2, Mobilenetv3Small, EfficientNetLite, PP-LCNet, SwinTransformer YOLO), Mod…☆1,019Apr 29, 2022Updated 3 years ago
- ☆14Oct 4, 2021Updated 4 years ago
- ☆751Mar 24, 2023Updated 2 years ago
- This repo would give multi-task keypoint detect code based yolov8. The landmarks or keypoints with different classes and numbers can be …☆12Feb 28, 2023Updated 2 years ago
- 🚀🚀🚀YOLOC is Combining different modules to build an different Object detection model.Including YOLOv3、YOLOv4、Scaled_YOLOv4、YOLOv5、YOLO…☆73Jul 31, 2022Updated 3 years ago
- YOLOv3、YOLOv4、YOLOv5、YOLOv5-Lite、YOLOv6-v1、YOLOv6-v2、YOLOv7、YOLOX、YOLOX-Lite、PP-YOLOE、PP-PicoDet-Plus、YOLO-Fastest v2、FastestDet、YOLOv5-S…☆764Oct 25, 2022Updated 3 years ago
- based on yolo-high-level project (detect\pose\classify\segment\):include yolov5\yolov7\yolov8\ core ,improvement research ,SwintransformV…☆758Feb 3, 2026Updated 2 weeks ago
- 🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.…☆17Feb 12, 2023Updated 3 years ago
- 基于YoloV5的一些魔改及相关部署方案☆63Mar 27, 2022Updated 3 years ago
- yolov5 prune,Support V2, V3, V4 and V6 versions of yolov5☆583Jan 6, 2022Updated 4 years ago
- 一些关于目标检测的脚本和改进思路代码,详细请看readme.md☆7,038Feb 9, 2026Updated last week
- Make it easier for yolov6 to change the network structure☆70Nov 11, 2024Updated last year
- Multi-backbone, Prune, Quantization, KD☆156May 23, 2022Updated 3 years ago
- 🚀Simple and efficient use for Ultralytics yolov8🚀☆172Sep 19, 2023Updated 2 years ago
- More readable and flexible yolov5 with more backbone(gcn, resnet, shufflenet, moblienet, efficientnet, hrnet, swin-transformer, etc) and …☆686Aug 19, 2024Updated last year
- 🚀🚀🚀 A collection of some awesome public YOLO object detection series projects and the related object detection datasets.☆1,691May 31, 2025Updated 8 months ago
- DEYOv1.5☆29Jul 22, 2024Updated last year
- ☆15May 17, 2021Updated 4 years ago
- yolov5模型训练后量化代码☆19Dec 6, 2020Updated 5 years ago
- OpenMMLab YOLO series toolbox and benchmark. Implemented RTMDet, RTMDet-Rotated,YOLOv5, YOLOv6, YOLOv7, YOLOv8,YOLOX, PPYOLOE, etc.☆3,410Jul 14, 2024Updated last year
- YOLO-FaceV2: A Scale and Occlusion Aware Face Detector☆234May 22, 2025Updated 8 months ago
- 🔥🔥🔥 专注于YOLO改进模型,Support to improve backbone, neck, head, loss, IoU, NMS and other modules🚀☆323Jan 28, 2025Updated last year
- yolov5 pruning (SFP Pruning、Nework Slimming)☆19Oct 5, 2021Updated 4 years ago
- Pytorch and ncnn implementation of PPYOLOE、YOLOX、PPYOLO、PPYOLOv2、PicoDet and so on.☆309Jul 20, 2025Updated 6 months ago
- yolov8seg 部署版本,便于移植不同平台(onnx、tensorRT、rknn、Horizon),全网部署最简单、速度最快的部署方式。☆11May 20, 2024Updated last year
- A lightweight vision library for performing large scale object detection & instance segmentation☆58Nov 2, 2023Updated 2 years ago
- RT-DETRv2 tensorrt C++ 部署☆23Oct 29, 2024Updated last year
- ☆92Jun 22, 2021Updated 4 years ago
- 手摸手 美团 YOLOv6模型训练和TensorRT端到端部署方案教程☆34Jun 30, 2022Updated 3 years ago
- ☆137Apr 25, 2022Updated 3 years ago
- ☆586Jan 5, 2022Updated 4 years ago
- yolov5第四版☆15Oct 13, 2021Updated 4 years ago
- ☆39May 21, 2023Updated 2 years ago
- [MICCAI'24] Official implementation of "BGF-YOLO: Enhanced YOLOv8 with Multiscale Attentional Feature Fusion for Brain Tumor Detection".☆142Nov 20, 2025Updated 2 months ago
- ☆15Jan 10, 2023Updated 3 years ago
- 深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,50余万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系sc…☆13Oct 14, 2021Updated 4 years ago
- 将YOLOv5-Lite代码中的head更换为YOLOX head☆22Mar 22, 2022Updated 3 years ago