注意数据集中大约1/3是原图剩余为增强图片，按照1:2增强

数据集格式：YOLO关键点格式(注意这个不是目标检测或者分割的YOLO格式，仅仅包含jpg图片以及对应的yolo格式txt文件)

图片数量(jpg文件个数)：2216

标注数量(txt文件个数)：2216

训练集数量：1937

验证集数量：186

测试集数量：93

标注类别数：1

标注类别名称:['cat']

标注的关键点数：37

关键点类别名:["right-base-r-ear","right-mid-r-ear","tip-r-ear","left-mid-r-ear","left-base-r-ear","back-r-ear","back-l-ear","right-base-l-ear","right-mid-l-ear","tip-l-ear","left-mid-l-ear","left-base-l-ear","lat-r-eye","med-r-eye","top-r-eye","bot-r-eye","med-l-eye","lat-l-eye","top-l-eye","bot-l-eye","top-r-muz","top-l-muz","top-muz","bot-muz","lat-r-muz","lat-l-muz","bot-r-muz","bot-l-muz","bot-r-whisk","top-r-whisk","top-l-whisk","bot-l-whisk","top-head","nose","chin","r-shoulder","l-shoulder"]

每个类别标注的框数：

cat 框数=2217

总框数=2217

图片分辨率：640x640

所在github仓库：firc-dataset

重要说明：数据集已经划分好训练验证测试集可以直接用于yolov5-pose或者yolov8-pose或者yolov11-pose或者yolov26-pose训练

特别声明：本数据集不对训练的模型或者权重文件精度作任何保证

图片预览：

标注例子：

原图（随机选16张图）：

标注绘制结果：