AI-exp-5/datasets/train/labels/-10-1_mp4-93_jpg.rf.3e735fabd4bf202a99401e2be9e1094c.txt

1 0.452102125 0.08113617643229167 0.4615699794921875 0.07868235677083334 0.44955440380859374 0.009742186197916667 0.44103333447265625 0.011950623046875 0.452102125 0.08113617643229167
0 0.5903156875 0.9820206582031249 0.6007303276367187 0.97932145703125 0.5915551083984375 0.9096451399739583 0.5792468974609375 0.91283510546875 0.5903156875 0.9820206582031249
2 0.4957675986328125 0.4615325703125 0.4852199423828125 0.4970181966145833 0.49813128369140625 0.5316641803385417 0.526113568359375 0.5348925305989584 0.5458652333984375 0.5153625592447917 0.8723954384765625 0.5512616842447916 0.8733954306640626 0.5379017311197917 0.549022642578125 0.4831023678385417 0.5253019848632813 0.45518811067708337 0.4957675986328125 0.4615325703125
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 0.452102125 0.08113617643229167 0.4615699794921875 0.07868235677083334 0.44955440380859374 0.009742186197916667 0.44103333447265625 0.011950623046875 0.452102125 0.08113617643229167`
			`0 0.5903156875 0.9820206582031249 0.6007303276367187 0.97932145703125 0.5915551083984375 0.9096451399739583 0.5792468974609375 0.91283510546875 0.5903156875 0.9820206582031249`
			`2 0.4957675986328125 0.4615325703125 0.4852199423828125 0.4970181966145833 0.49813128369140625 0.5316641803385417 0.526113568359375 0.5348925305989584 0.5458652333984375 0.5153625592447917 0.8723954384765625 0.5512616842447916 0.8733954306640626 0.5379017311197917 0.549022642578125 0.4831023678385417 0.5253019848632813 0.45518811067708337 0.4957675986328125 0.4615325703125`