目标跟踪Sort算法_车流量统计.zip
1、tiny_yolov4文件夹： 目标检测算法源码，包括：网络搭建、训练好的权重、解码文件、预测文件。
为提升算法速度，我摒弃了YOLOv4框架而采用了Tiny_YOLOv4框架，检测精度虽然有所下降，但每帧推理速度从0.17s提升至0.03s。
2、predict.py： 用于验证目标检测的效果，可单独独立出来运行，与目标跟踪无关。
3、kalman.py： 卡尔曼滤波器，基于恒速运动模型，预测下一帧目标物体的位置。
4、tracker.py： 存储每个时刻不同目标物体的状态，管理目标跟踪整个系统运作过程。
5、main.py： 整个项目的运行入口，直接运行main.py，就可以调用Tiny_YOLOv4 + Sort，处理视频流信息，完成目标跟踪、车流量统计。
6、MVI_39211、MVI_39031：DATRAC数据集测试集的两个视频，交通路段车流量画面。demo1、demo2：调用目标跟踪算法，车流量的每帧统计结果。
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