AI-exp-5/datasets/train/labels/-10-1_mp4-48_jpg.rf.f2fd8f3b2250dd936b01c17a038675e9.txt

2 0.5111453515625 0.48806916992187505 0.4952744970703125 0.4634584466145833 0.4636830395507813 0.46863037044270833 0.449272384765625 0.5020855611979167 0.4633291826171875 0.53865426171875 0.488202455078125 0.544947517578125 0.507365759765625 0.5314449127604167 0.8145771958007813 0.6806830371093749 0.8175836567382813 0.6711211796875 0.5162676000976563 0.50148291796875 0.5111453515625 0.48806916992187505
0 0.435474994140625 0.014582649088541668 0.42302987451171875 0.016620073567708334 0.43177901171875 0.07997102473958333 0.443266814453125 0.07809032486979166 0.435474994140625 0.014582649088541668
1 0.5264720366210938 0.918312416015625 0.5170164111328125 0.9211560885416666 0.5246737211914062 0.9937554466145833 0.53520420703125 0.9920314720052082 0.5264720366210938 0.918312416015625
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 0.5111453515625 0.48806916992187505 0.4952744970703125 0.4634584466145833 0.4636830395507813 0.46863037044270833 0.449272384765625 0.5020855611979167 0.4633291826171875 0.53865426171875 0.488202455078125 0.544947517578125 0.507365759765625 0.5314449127604167 0.8145771958007813 0.6806830371093749 0.8175836567382813 0.6711211796875 0.5162676000976563 0.50148291796875 0.5111453515625 0.48806916992187505`
			`0 0.435474994140625 0.014582649088541668 0.42302987451171875 0.016620073567708334 0.43177901171875 0.07997102473958333 0.443266814453125 0.07809032486979166 0.435474994140625 0.014582649088541668`
			`1 0.5264720366210938 0.918312416015625 0.5170164111328125 0.9211560885416666 0.5246737211914062 0.9937554466145833 0.53520420703125 0.9920314720052082 0.5264720366210938 0.918312416015625`