fall-detection-源码
人体跌倒检测与追踪
使用Tiny-YOLO oneclass检测帧中的每个人，并使用获取骨骼姿势，然后使用模型从每个人跟踪的每30帧中预测动作。
现在支持7种动作：站立，行走，坐着，躺下，站起来，坐下，跌倒。
先决条件
这些模型需要Python> 3.6和Pytorch> 1.3.1。 对于NVIDIA jetson设备，建议使用docker容器运行项目。 建造容器
cd ${current_repository_path}
./docker/build.sh
要运行容器，请使用以下命令
./docker/run.sh
该脚本会将工作目录安装到容器。
数据
该项目训练了一个新的Tiny-YOLO oneclass模型，以仅检测人的物体并减小模型的大小。 使用旋转增强的人员关键点数据集进行训练，以在各种角度姿势中更可靠地检测人员。
对于动作识别，使用来自跌倒检测数据集（，家庭）的数据，通
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资源详情
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