AI-exp-5/datasets/valid/labels/-10-1_mp4-105_jpg.rf.9cba4585b435f829039c85de1b8f2b74.txt

1 0.486111111328125 0.92463991796875 0.4783950615234375 0.9233539095052082 0.4783950615234375 0.9927983541666667 0.4870756171875 0.9927983541666667 0.486111111328125 0.92463991796875
0 0.4774305556640625 0.0025720162760416664 0.46682098779296877 0.003858024739583333 0.46971450634765627 0.07587448567708334 0.481288580078125 0.077160494140625 0.4774305556640625 0.0025720162760416664
2 0.4591049384765625 0.47067901236979165 0.44849537060546874 0.5015432096354167 0.46199845703125 0.5336934153645834 0.486111111328125 0.54140946484375 0.510223765625 0.5285493828125 0.5160108022460937 0.5002572018229167 0.5034722221679687 0.46939300390625 0.4783950615234375 0.45396090559895835 0.31732253076171874 0.077160494140625 0.30767746923828126 0.08230452669270834 0.4591049384765625 0.47067901236979165
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 0.486111111328125 0.92463991796875 0.4783950615234375 0.9233539095052082 0.4783950615234375 0.9927983541666667 0.4870756171875 0.9927983541666667 0.486111111328125 0.92463991796875`
			`0 0.4774305556640625 0.0025720162760416664 0.46682098779296877 0.003858024739583333 0.46971450634765627 0.07587448567708334 0.481288580078125 0.077160494140625 0.4774305556640625 0.0025720162760416664`
			`2 0.4591049384765625 0.47067901236979165 0.44849537060546874 0.5015432096354167 0.46199845703125 0.5336934153645834 0.486111111328125 0.54140946484375 0.510223765625 0.5285493828125 0.5160108022460937 0.5002572018229167 0.5034722221679687 0.46939300390625 0.4783950615234375 0.45396090559895835 0.31732253076171874 0.077160494140625 0.30767746923828126 0.08230452669270834 0.4591049384765625 0.47067901236979165`