AI-exp-5/datasets/train/labels/-10-1_mp4-48_jpg.rf.8a145bd7d9e778c078f7245775b5d377.txt

2 0.4887001796875 0.511669662109375 0.5042464799804688 0.5366459498697916 0.5359008227539063 0.5322099427083333 0.5507471875 0.499095181640625 0.537171189453125 0.4622049505208334 0.512384080078125 0.45533385546875 0.4930469541015625 0.4683884759114583 0.18783573095703124 0.3120243092447917 0.18470456982421876 0.32151475130208335 0.4837542880859375 0.4981387630208333 0.4887001796875 0.511669662109375
0 0.5581614028320312 0.9868449082031251 0.5706312954101562 0.985097390625 0.5627127104492188 0.9215524967447917 0.5512020405273438 0.9231655904947916 0.5581614028320312 0.9868449082031251
1 0.4790074140625 0.08113529427083334 0.4884988208007813 0.0785120859375 0.4817929521484375 0.0057456002604166665 0.4712415048828125 0.00722426953125 0.4790074140625 0.08113529427083334
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 0.4887001796875 0.511669662109375 0.5042464799804688 0.5366459498697916 0.5359008227539063 0.5322099427083333 0.5507471875 0.499095181640625 0.537171189453125 0.4622049505208334 0.512384080078125 0.45533385546875 0.4930469541015625 0.4683884759114583 0.18783573095703124 0.3120243092447917 0.18470456982421876 0.32151475130208335 0.4837542880859375 0.4981387630208333 0.4887001796875 0.511669662109375`
			`0 0.5581614028320312 0.9868449082031251 0.5706312954101562 0.985097390625 0.5627127104492188 0.9215524967447917 0.5512020405273438 0.9231655904947916 0.5581614028320312 0.9868449082031251`
			`1 0.4790074140625 0.08113529427083334 0.4884988208007813 0.0785120859375 0.4817929521484375 0.0057456002604166665 0.4712415048828125 0.00722426953125 0.4790074140625 0.08113529427083334`