ComView/datasets/train/labels/img5_jpg.rf.affd40ffd1771753c5d020790ee631af.txt

1 0.16105769230769232 0.125 0.11899038461538461 0.11057692307692307
1 0.09615384615384616 0.8545673076923077 0.1201923076923077 0.125
1 0.6466346153846154 0.4795673076923077 0.1141826923076923 0.11298076923076923
1 0.6358173076923077 0.8689903846153846 0.11658653846153846 0.125
1 0.8161057692307693 0.8641826923076923 0.13701923076923078 0.14423076923076922
0 0.33052884615384615 0.12980769230769232 0.1141826923076923 0.10697115384615384
0 0.6574519230769231 0.12860576923076922 0.10216346153846154 0.1141826923076923
0 0.6526442307692307 0.3004807692307692 0.11538461538461539 0.12740384615384615
0 0.8185096153846154 0.4855769230769231 0.11177884615384616 0.10817307692307693
0 0.27524038461538464 0.6670673076923077 0.10216346153846154 0.10817307692307693
0 0.09735576923076923 0.6598557692307693 0.13221153846153846 0.12379807692307693
0 0.47716346153846156 0.8533653846153846 0.11778846153846154 0.12259615384615384
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 0.16105769230769232 0.125 0.11899038461538461 0.11057692307692307`
			`1 0.09615384615384616 0.8545673076923077 0.1201923076923077 0.125`
			`1 0.6466346153846154 0.4795673076923077 0.1141826923076923 0.11298076923076923`
			`1 0.6358173076923077 0.8689903846153846 0.11658653846153846 0.125`
			`1 0.8161057692307693 0.8641826923076923 0.13701923076923078 0.14423076923076922`
			`0 0.33052884615384615 0.12980769230769232 0.1141826923076923 0.10697115384615384`
			`0 0.6574519230769231 0.12860576923076922 0.10216346153846154 0.1141826923076923`
			`0 0.6526442307692307 0.3004807692307692 0.11538461538461539 0.12740384615384615`
			`0 0.8185096153846154 0.4855769230769231 0.11177884615384616 0.10817307692307693`
			`0 0.27524038461538464 0.6670673076923077 0.10216346153846154 0.10817307692307693`
			`0 0.09735576923076923 0.6598557692307693 0.13221153846153846 0.12379807692307693`
			`0 0.47716346153846156 0.8533653846153846 0.11778846153846154 0.12259615384615384`