garlic-byte / yolov8_distillationLinks
轻量化剪枝+蒸馏
☆51Updated last year
Alternatives and similar repositories for yolov8_distillation
Users that are interested in yolov8_distillation are comparing it to the libraries listed below
Sorting:
- ☆99Updated last year
- ☆198Updated last year
- 本项目支持对剪枝后的yolov5模型进行知识蒸馏训练(This project supports knowledge distillation training for the pruned YOLOv5 model)☆106Updated last year
- Wise-IoU: Bounding Box Regression Loss with Dynamic Focusing Mechanism☆86Updated last year
- WIDER-FACE Face Detector Based On YOLOV8☆82Updated last year
- Pytorch implementation of the 'Slim-neck by GSConv: a lightweight-design for real-time detector architectures'☆230Updated 3 weeks ago
- ☆133Updated 3 months ago
- 🔥🔥🔥 专注于YOLO改进模型,Support to improve backbone, neck, head, loss, IoU, NMS and other modules🚀☆297Updated 8 months ago
- 一个修改YOLOv5以使用SwinTransformer模块的代码仓库。A repository that modifies YOLOv5 to use various SwinTransformer blocks.☆114Updated 3 weeks ago
- ☆251Updated 3 months ago
- 🌟Change the world, it will become a better place. | 以科研和竞赛为导向的最好的YOLO实践框架!☆238Updated last year
- 这是一个DETR-pytorch的仓库,可以训练自己的数据集☆209Updated 2 years ago
- This is an improvement strategy based on YOLOv8, which uses MobileNetv4 to improve the model. It can reduce the parameters of the model a…☆53Updated last year
- ☆38Updated 2 years ago
- Inner-IoU: More Effective Intersection over Union Loss with Auxiliary Bounding Box☆45Updated last year
- This is a repository for HIC-Yolov5☆53Updated last year
- ☁️💡🎈专注于改进YOLOv7,Support to improve Backbone, Neck, Head, Loss, IoU, NMS and other modules☆209Updated last year
- ☆56Updated last year
- 知识蒸馏复现相关☆27Updated 3 years ago
- 这个仓库用来整理研究时用过的一些数据集☆103Updated last year
- DEYOLO: Dual-Feature-Enhancement YOLO for Cross-Modality Object Detection☆126Updated 3 months ago
- YOLOV5 小目标检测修改版☆193Updated 4 years ago
- Multi-backbone, Prune, Quantization, KD☆156Updated 3 years ago
- Make it easier for yolov6 to change the network structure☆69Updated 10 months ago
- 在YOLOv7的基础上使用KLD损失修改为旋转目标检测yolov7-obb☆187Updated last year
- Use visible and infrared images to train the network. This method is better to face the dark environment.☆115Updated 2 years ago
- ☆181Updated 10 months ago
- The official implementation of CEASC☆132Updated 2 years ago
- 这是一个yolov5-v6.1-pytorch的源码,可以用于训练自己的模型。☆129Updated 2 years ago
- yolov8-prune☆18Updated 2 years ago