ComView/datasets/train/labels/trial00001_0001_jpg.rf.f40d7cca051f6c71ec8955cd34723ad3.txt

1 0.3629807692307692 0.15384615384615385 0.08413461538461539 0.14903846153846154
1 0.49278846153846156 0.1466346153846154 0.0829326923076923 0.14903846153846154
1 0.6286057692307693 0.14543269230769232 0.0889423076923077 0.15264423076923078
1 0.171875 0.7319711538461539 0.09615384615384616 0.15144230769230768
0 0.17307692307692307 0.5048076923076923 0.09014423076923077 0.14302884615384615
0 0.2980769230769231 0.5060096153846154 0.08533653846153846 0.14182692307692307
0 0.3004807692307692 0.7403846153846154 0.08533653846153846 0.140625
0 0.4254807692307692 0.5060096153846154 0.07932692307692307 0.13581730769230768
0 0.5576923076923077 0.5012019230769231 0.078125 0.1346153846153846
0 0.6959134615384616 0.5048076923076923 0.08653846153846154 0.13581730769230768
0 0.8269230769230769 0.5024038461538461 0.09495192307692307 0.14543269230769232
0 0.8305288461538461 0.7415865384615384 0.09375 0.1502403846153846
0 0.6959134615384616 0.7403846153846154 0.08533653846153846 0.1502403846153846
0 0.5625 0.7403846153846154 0.08533653846153846 0.14783653846153846
0 0.43028846153846156 0.7367788461538461 0.0829326923076923 0.14903846153846154
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 0.15384615384615385 0.08413461538461539 0.14903846153846154`
			`1 0.49278846153846156 0.1466346153846154 0.0829326923076923 0.14903846153846154`
			`1 0.6286057692307693 0.14543269230769232 0.0889423076923077 0.15264423076923078`
			`1 0.171875 0.7319711538461539 0.09615384615384616 0.15144230769230768`
			`0 0.17307692307692307 0.5048076923076923 0.09014423076923077 0.14302884615384615`
			`0 0.2980769230769231 0.5060096153846154 0.08533653846153846 0.14182692307692307`
			`0 0.3004807692307692 0.7403846153846154 0.08533653846153846 0.140625`
			`0 0.4254807692307692 0.5060096153846154 0.07932692307692307 0.13581730769230768`
			`0 0.5576923076923077 0.5012019230769231 0.078125 0.1346153846153846`
			`0 0.6959134615384616 0.5048076923076923 0.08653846153846154 0.13581730769230768`
			`0 0.8269230769230769 0.5024038461538461 0.09495192307692307 0.14543269230769232`
			`0 0.8305288461538461 0.7415865384615384 0.09375 0.1502403846153846`
			`0 0.6959134615384616 0.7403846153846154 0.08533653846153846 0.1502403846153846`
			`0 0.5625 0.7403846153846154 0.08533653846153846 0.14783653846153846`
			`0 0.43028846153846156 0.7367788461538461 0.0829326923076923 0.14903846153846154`