ComView/datasets/train/labels/trial00001_0005_jpg.rf.1ef906068263a1dc3d9573d2855cf685.txt

1 0.3629807692307692 0.14543269230769232 0.07932692307692307 0.14543269230769232
1 0.4963942307692308 0.14783653846153846 0.07932692307692307 0.14423076923076922
1 0.6262019230769231 0.14423076923076922 0.08413461538461539 0.14903846153846154
1 0.17067307692307693 0.7295673076923077 0.0889423076923077 0.14543269230769232
0 0.17307692307692307 0.5048076923076923 0.08774038461538461 0.12860576923076922
0 0.2956730769230769 0.5036057692307693 0.07932692307692307 0.12139423076923077
0 0.3016826923076923 0.7391826923076923 0.08774038461538461 0.14903846153846154
0 0.43149038461538464 0.7307692307692307 0.08653846153846154 0.140625
0 0.42788461538461536 0.5048076923076923 0.07932692307692307 0.13221153846153846
0 0.5576923076923077 0.5012019230769231 0.07932692307692307 0.140625
0 0.5625 0.7427884615384616 0.08533653846153846 0.13942307692307693
0 0.6911057692307693 0.7367788461538461 0.08052884615384616 0.14302884615384615
0 0.6935096153846154 0.5024038461538461 0.08533653846153846 0.1346153846153846
0 0.8257211538461539 0.5024038461538461 0.09615384615384616 0.15144230769230768
0 0.8269230769230769 0.7415865384615384 0.09014423076923077 0.14182692307692307
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 0.3629807692307692 0.14543269230769232 0.07932692307692307 0.14543269230769232`
			`1 0.4963942307692308 0.14783653846153846 0.07932692307692307 0.14423076923076922`
			`1 0.6262019230769231 0.14423076923076922 0.08413461538461539 0.14903846153846154`
			`1 0.17067307692307693 0.7295673076923077 0.0889423076923077 0.14543269230769232`
			`0 0.17307692307692307 0.5048076923076923 0.08774038461538461 0.12860576923076922`
			`0 0.2956730769230769 0.5036057692307693 0.07932692307692307 0.12139423076923077`
			`0 0.3016826923076923 0.7391826923076923 0.08774038461538461 0.14903846153846154`
			`0 0.43149038461538464 0.7307692307692307 0.08653846153846154 0.140625`
			`0 0.42788461538461536 0.5048076923076923 0.07932692307692307 0.13221153846153846`
			`0 0.5576923076923077 0.5012019230769231 0.07932692307692307 0.140625`
			`0 0.5625 0.7427884615384616 0.08533653846153846 0.13942307692307693`
			`0 0.6911057692307693 0.7367788461538461 0.08052884615384616 0.14302884615384615`
			`0 0.6935096153846154 0.5024038461538461 0.08533653846153846 0.1346153846153846`
			`0 0.8257211538461539 0.5024038461538461 0.09615384615384616 0.15144230769230768`
			`0 0.8269230769230769 0.7415865384615384 0.09014423076923077 0.14182692307692307`