Human-Falling-Detect-Tracks:AlphaPose + ST-GCN + SORT-源码

上传者: 42136365 | 上传时间: 2021-09-10 13:12:59 | 文件大小: 27.72MB | 文件类型: ZIP
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 Python> 3.6 火炬> 1.3.1 原始测试运行在:i7-8750H CPU @ 2.20GHz x12,GeForce RTX 2070 8GB,CUDA 10.2 数据 该项目已经训练了一个新的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,通过AlphaPose提取骨骼姿势,并手动标记每个动作帧,以训练ST-GCN模型。 预训练模型 Tiny-YOLO oneclass- , SPPE

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