AI-exp-5/datasets/train/labels/-10-1_mp4-39_jpg.rf.0cae5b09186822bb3060271be1e309c2.txt

2 0.8391203706054687 0.5195473248697916 0.5121527778320313 0.48482510286458336 0.5005787036132813 0.46167695442708334 0.46778549365234373 0.4591049381510417 0.4504243828125 0.505401234375 0.46392746923828126 0.54012345703125 0.492862654296875 0.54012345703125 0.511188271484375 0.5195473248697916 0.8391203706054687 0.5388374485677083 0.8391203706054687 0.5195473248697916
0 0.481288580078125 0.007716049479166666 0.46778549365234373 0.006430041015625 0.46971450634765627 0.07587448567708334 0.48225308642578124 0.07587448567708334 0.481288580078125 0.007716049479166666
1 0.48900462939453126 0.9207818932291666 0.4774305556640625 0.9207818932291666 0.4774305556640625 0.991512345703125 0.48900462939453126 0.991512345703125 0.48900462939453126 0.9207818932291666
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 0.8391203706054687 0.5195473248697916 0.5121527778320313 0.48482510286458336 0.5005787036132813 0.46167695442708334 0.46778549365234373 0.4591049381510417 0.4504243828125 0.505401234375 0.46392746923828126 0.54012345703125 0.492862654296875 0.54012345703125 0.511188271484375 0.5195473248697916 0.8391203706054687 0.5388374485677083 0.8391203706054687 0.5195473248697916`
			`0 0.481288580078125 0.007716049479166666 0.46778549365234373 0.006430041015625 0.46971450634765627 0.07587448567708334 0.48225308642578124 0.07587448567708334 0.481288580078125 0.007716049479166666`
			`1 0.48900462939453126 0.9207818932291666 0.4774305556640625 0.9207818932291666 0.4774305556640625 0.991512345703125 0.48900462939453126 0.991512345703125 0.48900462939453126 0.9207818932291666`