ComView/datasets/train/labels/img9_jpg.rf.93f4db67103133dd2c17e7048c72af0f.txt

1 0.15144230769230768 0.13221153846153846 0.13581730769230768 0.13701923076923078
1 0.8545673076923077 0.5108173076923077 0.12259615384615384 0.13942307692307693
0 0.3293269230769231 0.140625 0.12259615384615384 0.12740384615384615
0 0.6826923076923077 0.13942307692307693 0.1045673076923077 0.11899038461538461
0 0.6790865384615384 0.31490384615384615 0.1346153846153846 0.13581730769230768
0 0.6694711538461539 0.5072115384615384 0.1201923076923077 0.12139423076923077
0 0.28365384615384615 0.6935096153846154 0.12860576923076922 0.10697115384615384
0 0.078125 0.7007211538461539 0.1141826923076923 0.12379807692307693
0 0.09495192307692307 0.8990384615384616 0.12980769230769232 0.11057692307692307
0 0.47836538461538464 0.8966346153846154 0.11778846153846154 0.11778846153846154
0 0.6598557692307693 0.9134615384615384 0.14423076923076922 0.1310096153846154
0 0.8509615384615384 0.9182692307692307 0.15745192307692307 0.1466346153846154
feat(datasets): 添加新的训练数据标签 - 在 datasets/train/labels 目录下新增了多个标签文件 - 文件命名格式为：视频ID-帧序号.jpg.rf.哈希值.txt -标签内容包括物体类别和位置信息，用于训练目标检测模型 2025-05-29 11:59:57 +00:00			`1 0.15144230769230768 0.13221153846153846 0.13581730769230768 0.13701923076923078`
			`1 0.8545673076923077 0.5108173076923077 0.12259615384615384 0.13942307692307693`
			`0 0.3293269230769231 0.140625 0.12259615384615384 0.12740384615384615`
			`0 0.6826923076923077 0.13942307692307693 0.1045673076923077 0.11899038461538461`
			`0 0.6790865384615384 0.31490384615384615 0.1346153846153846 0.13581730769230768`
			`0 0.6694711538461539 0.5072115384615384 0.1201923076923077 0.12139423076923077`
			`0 0.28365384615384615 0.6935096153846154 0.12860576923076922 0.10697115384615384`
			`0 0.078125 0.7007211538461539 0.1141826923076923 0.12379807692307693`
			`0 0.09495192307692307 0.8990384615384616 0.12980769230769232 0.11057692307692307`
			`0 0.47836538461538464 0.8966346153846154 0.11778846153846154 0.11778846153846154`
			`0 0.6598557692307693 0.9134615384615384 0.14423076923076922 0.1310096153846154`
			`0 0.8509615384615384 0.9182692307692307 0.15745192307692307 0.1466346153846154`