ByteTrack超详细教程！训练自己的数据集&&摄像头实时检测跟踪

### 1. datasets
           └——————VOCdevkit
           |         └——————VOC2012
           |                   └——————Annotations
           |                   └——————ImageSets
           |                                 └——————Main
           |                   └——————JPEGImages
                               └—————— divide_dataset.py

The COCO pretrained YOLOX model can be downloaded from their [model zoo](https://github.com/Megvii-BaseDetection/YOLOX/tree/0.1.0). After downloading the pretrained models, you can put them under 
   
    /pretrained.

   

根据需求修改文件yolox_voc_s_ZZH.py的种类数，在路径"exps/example/custom/"文件夹下

class Exp(MyExp):
    def __init__(self):
        super(Exp, self).__init__()
        self.num_classes = 2 #在这进行修改
        self.depth = 0.33
        self.width = 0.50
        self.warmup_epochs = 1

取消注释ZZH_track.py第227行代码，并注释第228行代码

```shell
cd 
   
    

python3 ZZH_track.py video -f exps/example/custom/yolox_voc_s_ZZH.py -c YOLOX_outputs/yolox_voc_s_ZZH/latest_ckpt.pth.tar --fp16 --fuse --save_result

   

@article{zhang2021bytetrack,
  title={ByteTrack: Multi-Object Tracking by Associating Every Detection Box},
  author={Zhang, Yifu and Sun, Peize and Jiang, Yi and Yu, Dongdong and Yuan, Zehuan and Luo, Ping and Liu, Wenyu and Wang, Xinggang},
  journal={arXiv preprint arXiv:2110.06864},
  year={2021}
}