AI-exp-5/datasets/train/labels/-10-1_mp4-77_jpg.rf.778ac8d649ec2b307cb81570dee093c8.txt

2 0.4873697548828125 0.491813875 0.4924505126953125 0.5324250911458334 0.5215639287109375 0.5461485813802084 0.5448400263671875 0.5307908860677083 0.5503284643554688 0.49141258268229165 0.7968042231445313 0.20259790169270833 0.7908349321289062 0.19028328971354166 0.530955380859375 0.4620433509114583 0.5036316635742187 0.465310599609375 0.4873697548828125 0.491813875
1 0.5395876586914062 0.07964690885416667 0.5500727919921875 0.08216093684895832 0.5557411142578125 0.010530603515625 0.5413285747070312 0.008849358072916666 0.5395876586914062 0.07964690885416667
0 0.488298796875 0.9940903522135417 0.4988679921875 0.9953232656250001 0.503491416015625 0.924861962890625 0.493883056640625 0.9237411334635417 0.488298796875 0.9940903522135417
feat(datasets): 添加新的训练和验证数据标签 - 在 train 和 valid 文件夹中添加了多个新的标签文件 - 标签文件包含了不同类型的目标检测框坐标和类别 - 新增数据有助于模型训练和性能提升 2025-06-06 10:07:28 +00:00			`2 0.4873697548828125 0.491813875 0.4924505126953125 0.5324250911458334 0.5215639287109375 0.5461485813802084 0.5448400263671875 0.5307908860677083 0.5503284643554688 0.49141258268229165 0.7968042231445313 0.20259790169270833 0.7908349321289062 0.19028328971354166 0.530955380859375 0.4620433509114583 0.5036316635742187 0.465310599609375 0.4873697548828125 0.491813875`
			`1 0.5395876586914062 0.07964690885416667 0.5500727919921875 0.08216093684895832 0.5557411142578125 0.010530603515625 0.5413285747070312 0.008849358072916666 0.5395876586914062 0.07964690885416667`
			`0 0.488298796875 0.9940903522135417 0.4988679921875 0.9953232656250001 0.503491416015625 0.924861962890625 0.493883056640625 0.9237411334635417 0.488298796875 0.9940903522135417`