# yolox-deepsort

**Repository Path**: tomprisoner/yolox-deepsort

## Basic Information

- **Project Name**: yolox-deepsort
- **Description**: No description available
- **Primary Language**: Python
- **License**: Apache-2.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-08-12
- **Last Updated**: 2021-08-12

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# 项目简介：
使用YOLOX+Deepsort实现车辆行人追踪和计数，代码封装成一个Detector类，更容易嵌入到自己的项目中。

代码地址（欢迎star）：

[https://github.com/Sharpiless/yolox-deepsort/](https://github.com/Sharpiless/yolox-deepsort/)

最终效果：

![在这里插入图片描述](https://img-blog.csdnimg.cn/7768e8e4cf0a4bbf97bb10ab56ea028c.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80NDkzNjg4OQ==,size_16,color_FFFFFF,t_70)

# 运行demo：

```bash
python demo.py
```

# 下载预训练模型：

|Model |size |mAP<sup>test<br>0.5:0.95 | Speed V100<br>(ms) | Params<br>(M) |FLOPs<br>(G)| weights |
| ------        |:---: | :---:       |:---:     |:---:  | :---: | :----: |
|[YOLOX-s](./exps/default/yolox_s.py)    |640  |39.6      |9.8     |9.0 | 26.8 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EW62gmO2vnNNs5npxjzunVwB9p307qqygaCkXdTO88BLUg?e=NMTQYw)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_s.pth) |
|[YOLOX-m](./exps/default/yolox_m.py)    |640  |46.4      |12.3     |25.3 |73.8| [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/ERMTP7VFqrVBrXKMU7Vl4TcBQs0SUeCT7kvc-JdIbej4tQ?e=1MDo9y)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_m.pth) |
|[YOLOX-l](./exps/default/yolox_l.py)    |640  |50.0  |14.5 |54.2| 155.6 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EWA8w_IEOzBKvuueBqfaZh0BeoG5sVzR-XYbOJO4YlOkRw?e=wHWOBE)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_l.pth) |
|[YOLOX-x](./exps/default/yolox_x.py)   |640  |**51.2**      | 17.3 |99.1 |281.9 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EdgVPHBziOVBtGAXHfeHI5kBza0q9yyueMGdT0wXZfI1rQ?e=tABO5u)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_x.pth) |
|[YOLOX-Darknet53](./exps/default/yolov3.py)   |640  | 47.4      | 11.1 |63.7 | 185.3 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EZ-MV1r_fMFPkPrNjvbJEMoBLOLAnXH-XKEB77w8LhXL6Q?e=mf6wOc)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_darknet53.pth) |

下载 yolox_s.pth 放到 weights 文件夹下
  
下载 [https://github.com/Sharpiless/Yolov5-Deepsort/blob/main/deep_sort/deep_sort/deep/checkpoint/ckpt.t7](https://github.com/Sharpiless/Yolov5-Deepsort/blob/main/deep_sort/deep_sort/deep/checkpoint/ckpt.t7) 放到 deep_sort/deep_sort/deep/checkpoint 文件夹下
  
# 训练自己的模型：


训练好后放到 weights 文件夹下

# 调用接口：

## 创建检测器：

```python
from AIDetector_pytorch import Detector

det = Detector()
```

## 调用检测接口：

```python
result = det.feedCap(im)
```

其中 im 为 BGR 图像

返回的 result 是字典，result['frame'] 返回可视化后的图像

# 联系作者：

> B站：[https://space.bilibili.com/470550823](https://space.bilibili.com/470550823)

> CSDN：[https://blog.csdn.net/weixin_44936889](https://blog.csdn.net/weixin_44936889)

> AI Studio：[https://aistudio.baidu.com/aistudio/personalcenter/thirdview/67156](https://aistudio.baidu.com/aistudio/personalcenter/thirdview/67156)

> Github：[https://github.com/Sharpiless](https://github.com/Sharpiless)