ComView/datasets/train/labels/trial01_0005_jpg.rf.c0842a2ac1baa29f12e9e88f9b9a7435.txt

1 0.5444711538461539 0.28725961538461536 0.04447115384615385 0.09375
1 0.6141826923076923 0.25961538461538464 0.052884615384615384 0.10096153846153846
1 0.7007211538461539 0.24278846153846154 0.06490384615384616 0.11057692307692307
1 0.5793269230769231 0.5132211538461539 0.055288461538461536 0.09014423076923077
1 0.8641826923076923 0.7271634615384616 0.0889423076923077 0.14302884615384615
0 0.46153846153846156 0.5084134615384616 0.040865384615384616 0.08774038461538461
0 0.515625 0.5096153846153846 0.04807692307692308 0.09495192307692307
0 0.6526442307692307 0.5096153846153846 0.0625 0.11177884615384616
0 0.7439903846153846 0.5084134615384616 0.07572115384615384 0.11177884615384616
0 0.8605769230769231 0.5108173076923077 0.08173076923076923 0.13221153846153846
0 0.45913461538461536 0.6346153846153846 0.04927884615384615 0.08533653846153846
0 0.515625 0.6514423076923077 0.04807692307692308 0.09014423076923077
0 0.5805288461538461 0.6646634615384616 0.057692307692307696 0.10817307692307693
0 0.6550480769230769 0.6778846153846154 0.06610576923076923 0.11538461538461539
0 0.7463942307692307 0.6959134615384616 0.0673076923076923 0.11899038461538461
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 0.5444711538461539 0.28725961538461536 0.04447115384615385 0.09375`
			`1 0.6141826923076923 0.25961538461538464 0.052884615384615384 0.10096153846153846`
			`1 0.7007211538461539 0.24278846153846154 0.06490384615384616 0.11057692307692307`
			`1 0.5793269230769231 0.5132211538461539 0.055288461538461536 0.09014423076923077`
			`1 0.8641826923076923 0.7271634615384616 0.0889423076923077 0.14302884615384615`
			`0 0.46153846153846156 0.5084134615384616 0.040865384615384616 0.08774038461538461`
			`0 0.515625 0.5096153846153846 0.04807692307692308 0.09495192307692307`
			`0 0.6526442307692307 0.5096153846153846 0.0625 0.11177884615384616`
			`0 0.7439903846153846 0.5084134615384616 0.07572115384615384 0.11177884615384616`
			`0 0.8605769230769231 0.5108173076923077 0.08173076923076923 0.13221153846153846`
			`0 0.45913461538461536 0.6346153846153846 0.04927884615384615 0.08533653846153846`
			`0 0.515625 0.6514423076923077 0.04807692307692308 0.09014423076923077`
			`0 0.5805288461538461 0.6646634615384616 0.057692307692307696 0.10817307692307693`
			`0 0.6550480769230769 0.6778846153846154 0.06610576923076923 0.11538461538461539`
			`0 0.7463942307692307 0.6959134615384616 0.0673076923076923 0.11899038461538461`