Spatio-temporal action detection is an important and challenging problem in video understanding. However, the application of the existing large-scale spatio-temporal action datasets in specific fields is limited, and there is currently no public tool for making spatio-temporal action datasets, it takes a lot of time and effort for researchers to customize the spatio-temporal action datasets, so we propose a multi-Person video dataset Annotation Method of spatio-temporally actions.First, we use ffmpeg to crop the videos and frame the videos; then use yolov5 to detect human in the video frame, and then use deep sort to detect the ID of the human in the video frame. By processing the detection results of yolov5 and deep sort, we can get the annotation file of the spatio-temporal action dataset to complete the work of customizing the spatio-temporal action dataset. https://github.com/Whiffe/Custom-ava-dataset_Custom-Spatio-Temporally-Action-Video-Dataset
翻译：Spatio- 时间- 时间- 时间- 时间- 行动探测是视频理解中一个重要且具有挑战性的问题。 然而, 目前在特定领域的大规模 spatio- 时间- 时间- 时间动作数据集的应用有限, 目前没有公共工具来建立 spatio- 时间- 时间动作数据集, 研究人员需要花很多时间和精力来定制spatio- 时间- 时间- 时间动作数据集, 因此我们提议一个多人视频数据集 spotio- 时间- 时间- 时间- 动作的批注方法。 首先, 我们使用 ffmpeg 来制作视频和框框; 然后使用 Yolov5 在视频框中探测人类, 然后使用深层次的某种工具来检测视频框中的人类身份 。 通过处理 Yolov5 的检测结果和深度排序, 我们可以得到spotio- 时间- 时间- 动作数据集的批注文件, 以完成调制spattio- 时间- 动作数据集的工作 。 https://github. com/ Whiffer/ Custo- ava- data- data- dataset_ Customtoom- Suption_ Sup_ Customomomomom- Stopomomomom- Satom- Set- Set- Set- Satom- Satom- set- Satom- Satom- Satom- Satom- setom- setom- setom- set- setom)- setom- setom- setom- setom- setom- setom- setom- setom- setom- setom- setom- set- set- set- set- set- set- set- set- setom- setom- set- set- set- set- set- set- set- set- set- set- set- set- set- set- set- set- set- set- set- set- set- set- set- set- set- set- set- s
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