AI-exp-5/datasets/train/labels/-10-1_mp4-34_jpg.rf.fe0c5bd86a7a0cb563424a7af0d46ccd.txt

2 0.5206443227539063 0.558349458984375 0.537409029296875 0.529596939453125 0.527020337890625 0.4954756328125 0.5040586958007812 0.47736873046875 0.3759850087890625 0.0791613828125 0.365089224609375 0.08564055143229167 0.4786352006835938 0.49248678971354165 0.4735463276367187 0.53547030078125 0.48896419921875 0.563185845703125 0.5206443227539063 0.558349458984375
0 0.13774570947265624 0.6105003717447917 0.14070537890625 0.625474708984375 0.19629931640625 0.61632196875 0.19395452978515626 0.5985913763020834 0.13774570947265624 0.6105003717447917
1 0.8141535859375 0.4449458587239583 0.8164433173828125 0.45485431315104163 0.8698025791015624 0.4436152565104166 0.8681277314453125 0.4309505475260416 0.8141535859375 0.4449458587239583
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 0.5206443227539063 0.558349458984375 0.537409029296875 0.529596939453125 0.527020337890625 0.4954756328125 0.5040586958007812 0.47736873046875 0.3759850087890625 0.0791613828125 0.365089224609375 0.08564055143229167 0.4786352006835938 0.49248678971354165 0.4735463276367187 0.53547030078125 0.48896419921875 0.563185845703125 0.5206443227539063 0.558349458984375`
			`0 0.13774570947265624 0.6105003717447917 0.14070537890625 0.625474708984375 0.19629931640625 0.61632196875 0.19395452978515626 0.5985913763020834 0.13774570947265624 0.6105003717447917`
			`1 0.8141535859375 0.4449458587239583 0.8164433173828125 0.45485431315104163 0.8698025791015624 0.4436152565104166 0.8681277314453125 0.4309505475260416 0.8141535859375 0.4449458587239583`