AI-exp-5/datasets/train/labels/-10-1_mp4-72_jpg.rf.54908fa028b92a8309adcf2d62542252.txt

0 0.45991330615234377 0.0059782858072916665 0.44739191015625 0.006853244140625 0.45325968603515626 0.08242183268229167 0.4638547138671875 0.08168148372395834 0.45991330615234377 0.0059782858072916665
1 0.5026466625976562 0.9211744108072916 0.49504214404296876 0.9242813378906249 0.497868931640625 0.9961991028645834 0.5075007758789063 0.9955260579427083 0.5026466625976562 0.9211744108072916
2 0.5094626748046875 0.480279734375 0.4843734990234375 0.4562774303385417 0.4589732612304688 0.4735056009114584 0.44943827880859377 0.501215111328125 0.4592679404296875 0.5301470247395833 0.32425564404296875 0.92848875390625 0.33332813037109377 0.93815698046875 0.4831415400390625 0.5477954049479167 0.5102157543945313 0.524011396484375 0.5094626748046875 0.480279734375
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 0.45991330615234377 0.0059782858072916665 0.44739191015625 0.006853244140625 0.45325968603515626 0.08242183268229167 0.4638547138671875 0.08168148372395834 0.45991330615234377 0.0059782858072916665`
			`1 0.5026466625976562 0.9211744108072916 0.49504214404296876 0.9242813378906249 0.497868931640625 0.9961991028645834 0.5075007758789063 0.9955260579427083 0.5026466625976562 0.9211744108072916`
			`2 0.5094626748046875 0.480279734375 0.4843734990234375 0.4562774303385417 0.4589732612304688 0.4735056009114584 0.44943827880859377 0.501215111328125 0.4592679404296875 0.5301470247395833 0.32425564404296875 0.92848875390625 0.33332813037109377 0.93815698046875 0.4831415400390625 0.5477954049479167 0.5102157543945313 0.524011396484375 0.5094626748046875 0.480279734375`