ComView/datasets/train/labels/img2_jpg.rf.d61e18b4a7647113e63feab6ca5735d0.txt

1 0.1466346153846154 0.13701923076923078 0.17307692307692307 0.15504807692307693
1 0.8725961538461539 0.13221153846153846 0.140625 0.14302884615384615
1 0.6730769230769231 0.5036057692307693 0.13942307692307693 0.13822115384615385
1 0.859375 0.5036057692307693 0.12740384615384615 0.13701923076923078
0 0.3329326923076923 0.13701923076923078 0.11298076923076923 0.11658653846153846
0 0.6826923076923077 0.12980769230769232 0.11899038461538461 0.11899038461538461
0 0.6778846153846154 0.3088942307692308 0.11298076923076923 0.11538461538461539
0 0.27524038461538464 0.6983173076923077 0.11298076923076923 0.12139423076923077
0 0.0829326923076923 0.6947115384615384 0.140625 0.12860576923076922
0 0.08413461538461539 0.8966346153846154 0.11899038461538461 0.109375
0 0.4855769230769231 0.8954326923076923 0.1141826923076923 0.1141826923076923
0 0.6622596153846154 0.9086538461538461 0.12259615384615384 0.125
0 0.8569711538461539 0.9110576923076923 0.15264423076923078 0.14783653846153846
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 0.1466346153846154 0.13701923076923078 0.17307692307692307 0.15504807692307693`
			`1 0.8725961538461539 0.13221153846153846 0.140625 0.14302884615384615`
			`1 0.6730769230769231 0.5036057692307693 0.13942307692307693 0.13822115384615385`
			`1 0.859375 0.5036057692307693 0.12740384615384615 0.13701923076923078`
			`0 0.3329326923076923 0.13701923076923078 0.11298076923076923 0.11658653846153846`
			`0 0.6826923076923077 0.12980769230769232 0.11899038461538461 0.11899038461538461`
			`0 0.6778846153846154 0.3088942307692308 0.11298076923076923 0.11538461538461539`
			`0 0.27524038461538464 0.6983173076923077 0.11298076923076923 0.12139423076923077`
			`0 0.0829326923076923 0.6947115384615384 0.140625 0.12860576923076922`
			`0 0.08413461538461539 0.8966346153846154 0.11899038461538461 0.109375`
			`0 0.4855769230769231 0.8954326923076923 0.1141826923076923 0.1141826923076923`
			`0 0.6622596153846154 0.9086538461538461 0.12259615384615384 0.125`
			`0 0.8569711538461539 0.9110576923076923 0.15264423076923078 0.14783653846153846`