AI-exp-5/datasets/train/labels/-10-1_mp4-17_jpg.rf.b5dda77882845484210c72db8a297fba.txt

2 0.4579167734375 0.5264636067708334 0.49222206494140625 0.5401302421874999 0.5150784565429688 0.5019068372395833 0.5103384711914063 0.48215714583333336 0.7300789731445313 0.15527095442708333 0.7205626088867187 0.14074128841145833 0.4911052109375 0.4543557194010417 0.47675323828125 0.451602982421875 0.45072472509765626 0.4849831653645833 0.4579167734375 0.5264636067708334
0 0.55826062890625 0.014544443359375 0.5433662905273438 0.00900851953125 0.535568376953125 0.07647965885416667 0.548776388671875 0.08022292447916667 0.55826062890625 0.014544443359375
1 0.4234302666015625 0.9097966165364584 0.4111656845703125 0.9063207265625 0.4004782514648437 0.9795466438802083 0.41368626318359375 0.9832899095052082 0.4234302666015625 0.9097966165364584
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 0.4579167734375 0.5264636067708334 0.49222206494140625 0.5401302421874999 0.5150784565429688 0.5019068372395833 0.5103384711914063 0.48215714583333336 0.7300789731445313 0.15527095442708333 0.7205626088867187 0.14074128841145833 0.4911052109375 0.4543557194010417 0.47675323828125 0.451602982421875 0.45072472509765626 0.4849831653645833 0.4579167734375 0.5264636067708334`
			`0 0.55826062890625 0.014544443359375 0.5433662905273438 0.00900851953125 0.535568376953125 0.07647965885416667 0.548776388671875 0.08022292447916667 0.55826062890625 0.014544443359375`
			`1 0.4234302666015625 0.9097966165364584 0.4111656845703125 0.9063207265625 0.4004782514648437 0.9795466438802083 0.41368626318359375 0.9832899095052082 0.4234302666015625 0.9097966165364584`