# introduction_yolo

**Repository Path**: xiaolixi/introduction_yolo

## Basic Information

- **Project Name**: introduction_yolo
- **Description**: introduction yolo
- **Primary Language**: Java
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-01-02
- **Last Updated**: 2025-01-03

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

以下是 YOLO 系列模型从 YOLOv1 到 YOLOv8 的相关论文和开源资源链接：

1. YOLOv1: You Only Look Once: Unified, Real-Time Object Detection
   - 论文链接: http://[YOLOv1 (2016)](https://arxiv.org/abs/1506.02640)
   - GitHub链接: https://github.com/pjreddie/darknet

![输入图片说明](imagesv1_param_image.png)
![输入图片说明](imagesreal_v1_param_description.png)

## 疑问点
1. 一个cell只能预测一个类别，那如果有两个类别的中心点都在一个cell里面怎么办？
2. 两个框公用一个类别，这个不会有问题吗？

 2. YOLOv2: YOLO9000: Better, Faster, Stronger
   - 论文链接: [YOLOv2 (2017)](https://arxiv.org/abs/1612.08242)
   - GitHub链接: https://github.com/pjreddie/darknet

3. YOLOv3: An Incremental Improvement
   - 论文链接: [YOLOv3 (2018)](https://arxiv.org/abs/1804.02767)
   - GitHub链接:https://github.com/pjreddie/darknet

4. YOLOv4: Optimal Speed and Accuracy of Object Detection
   -论文链接: [YOLOv4 (2020)](https://arxiv.org/abs/2004.10934)
   - GitHub链接: https://github.com/AlexeyAB/darknet

 5. YOLOv5: Ultralytics release (无正式论文)
   - YOLOv5 并没有正式发表的论文，主要是由 Ultralytics 团队通过 GitHub 进行发布和维护。
   - GitHub链接:[YOLOv5 GitHub](https://github.com/ultralytics/yolov5)

6. YOLOv6: A Hardware-Aware Efficient Object Detection Model
   - 论文链接:[YOLOv6 (2022)](https://arxiv.org/abs/2209.02976)
   - GitHub链接:https://github.com/meituan/YOLOv6

 7. YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
   - 论文链接: [YOLOv7 (2022)](https://arxiv.org/abs/2207.02696)
   - GitHub链接: https://github.com/WongKinYiu/yolov7

 8. YOLOv8: Latest Version by Ultralytics
   - YOLOv8 是 Ultralytics 发布的最新 YOLO 版本，同样没有正式的论文发布。它是 YOLO 系列的进一步改进，集成了多项新技术和特性。
   - GitHub链接:[YOLOv8 GitHub](https://github.com/ultralytics/ultralytics)