TTNet-Real-time-Analysis-System-for-Table-Tennis-Pytorch:“ TTNet”的非正式实施-源码

上传者: 42151373 | 上传时间: 2021-06-06 22:22:44 | 文件大小: 21.98MB | 文件类型: ZIP
TTNet-Pytorch 论文“ TTNet:乒乓球的实时时空视频分析”的实现可以在找到该项目的简介 演示版 1.特点 球检测全球舞台 检球局部阶段(细化) 事件发现检测(跳动和净匹配) 语义细分(人,表和记分板) 启用/禁用TTNet模型中的模块 平滑标记事件发现 TensorboardX (更新2020.06.23) :训练更快,在单个GPU(GTX1080Ti)的推理阶段达到> 120 FPS 。 (更新2020.07.03) :该实现可以与TTNet论文中报告的结果取得比较结果。 (更新2020.07.06) :TTNet Paper有几个限制(提示:损失函数,输入大小以及另外2个)。 我已经用新方法和新模型实施了该任务。 现在,新模型可以实现: > 130FPS推论, 细分任务的IoU得分约为0.96 球检测任务的均方根误差(RMSE) < 4像

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