AI-exp-5/datasets/train/labels/-10-1_mp4-13_jpg.rf.344a426cc07c1c1d3189ebe79ded4b41.txt

0 0.5708689541015625 0.9838419309895833 0.5821961567382813 0.980420705078125 0.575081791015625 0.9129255813802084 0.5597998764648437 0.9157892259114583 0.5708689541015625 0.9838419309895833
1 0.45753991845703124 0.010315134765625 0.4653409375 0.07508429427083334 0.47693660693359374 0.07421005403645833 0.4698222412109375 0.0067149316406250005 0.45753991845703124 0.010315134765625
2 0.5443216787109375 0.47325387760416665 0.51584878125 0.45261641927083335 0.4878508715820313 0.47344664453125 0.48480481982421875 0.4999903684895833 0.4978460830078125 0.5313114062500001 0.4319171015625 0.95923259375 0.43913987255859377 0.9630737213541667 0.5264841860351562 0.5350355013020833 0.5454678330078125 0.521089025390625 0.5443216787109375 0.47325387760416665
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			`0 0.5708689541015625 0.9838419309895833 0.5821961567382813 0.980420705078125 0.575081791015625 0.9129255813802084 0.5597998764648437 0.9157892259114583 0.5708689541015625 0.9838419309895833`
			`1 0.45753991845703124 0.010315134765625 0.4653409375 0.07508429427083334 0.47693660693359374 0.07421005403645833 0.4698222412109375 0.0067149316406250005 0.45753991845703124 0.010315134765625`
			`2 0.5443216787109375 0.47325387760416665 0.51584878125 0.45261641927083335 0.4878508715820313 0.47344664453125 0.48480481982421875 0.4999903684895833 0.4978460830078125 0.5313114062500001 0.4319171015625 0.95923259375 0.43913987255859377 0.9630737213541667 0.5264841860351562 0.5350355013020833 0.5454678330078125 0.521089025390625 0.5443216787109375 0.47325387760416665`