AI-exp-5/datasets/train/labels/-10-1_mp4-31_jpg.rf.4653c0b6799301aa34e17849a6c55633.txt

1 0.5037108032226563 0.9236755976562501 0.493115775390625 0.9244159466145834 0.4976670185546875 0.9910621191406249 0.509275708984375 0.9915387115885417 0.5037108032226563 0.9236755976562501
0 0.4600647412109375 0.009831023437500001 0.44658016064453127 0.010773285807291666 0.4541723916015625 0.08107028255208333 0.4618778662109375 0.08053184635416667 0.4600647412109375 0.009831023437500001
2 0.453497025390625 0.48161490234375 0.45825427734375 0.528930083984375 0.48405424609375 0.5464438541666666 0.5095554399414063 0.53178417578125 0.5130084462890625 0.4967730162760417 0.7971301162109375 0.27989015429687497 0.7907957485351562 0.26616727734375 0.5040410122070312 0.46520530729166665 0.47960805517578126 0.45789819856770836 0.453497025390625 0.48161490234375
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			`1 0.5037108032226563 0.9236755976562501 0.493115775390625 0.9244159466145834 0.4976670185546875 0.9910621191406249 0.509275708984375 0.9915387115885417 0.5037108032226563 0.9236755976562501`
			`0 0.4600647412109375 0.009831023437500001 0.44658016064453127 0.010773285807291666 0.4541723916015625 0.08107028255208333 0.4618778662109375 0.08053184635416667 0.4600647412109375 0.009831023437500001`
			`2 0.453497025390625 0.48161490234375 0.45825427734375 0.528930083984375 0.48405424609375 0.5464438541666666 0.5095554399414063 0.53178417578125 0.5130084462890625 0.4967730162760417 0.7971301162109375 0.27989015429687497 0.7907957485351562 0.26616727734375 0.5040410122070312 0.46520530729166665 0.47960805517578126 0.45789819856770836 0.453497025390625 0.48161490234375`