Detection On Tracks 轨道上的人类行为检测数据集

该数据集旨在检测铁路轨道上人员的计算机视觉模型，主要目标是通过提供高质量的带注释图像来提高铁路安全性，这些图像可用于训练模型以实时检测未经授权的人为干预，从而防止事故和死亡。

This dataset is designed for computer vision models that detect individuals on railway tracks. Its primary goal is to enhance railway safety by providing high-quality annotated images, which can be used to train models for real-time detection of unauthorized human interventions, thereby preventing accidents and fatalities.

搜集汇总

背景与挑战

背景概述

该数据集包含3,766张铁路轨道上人类行为的图片，分辨率为1,080×1,080，带有边界框注释，共分为4个类别。适用于训练和评估物体检测模型，特别是基于CNN和YOLO架构的模型，旨在提高铁路安全性。