EDIS-Net for Lane Markings Detection

The dataset of around 15.3K image frames is created from Malaysia's different places to test the framework. For instance, the videos were taken at Melaka KL expressway, KL-KLIA, Melaka-JB expressway, Melaka-Muar, Sungai Udang, Jalan UPM and Jalan Ayer Keroh. A high-resolution mobile camera was mounted beside the steering to capture the videos of lane markings. It can record the video in different resolutions like 4k, 60/30 fps and 1080/720, 30/60/240 fps. The videos were taken in the mode of 1080, 30 fps, and converted into 1920 ×1080 image frames. Then, the image frames' dimension is changed into 224×224 to make it compatible with the framework. The dataset is classified into three categories: lane markings pattern, illumination variation, and natural climate. The lane markings pattern contains 7.9k image frames of the solid lane, double line lane, curve lane, and vehicle obstacle. Again, illumination variation includes 5k image frames of low light, dark light, and cloudy. And about 2.5k rainy image frames are arranged in the natural climate category. All the images are in jpg form.本数据集包含约15300个图像帧 (image frames)，采集自马来西亚境内多个不同地点，用于测试该算法框架。示例采集点位包括马六甲（Melaka）境内的吉隆坡（KL）高速公路、吉隆坡-吉隆坡国际机场（KL-KLIA）高速公路、马六甲-柔佛（JB）高速公路、马六甲-麻坡（Muar）路段、双溪乌浪（Sungai Udang）、博特拉大学路（Jalan UPM）以及亚逸凯路（Jalan Ayer Keroh）。 研发人员将一台高分辨率手机摄像头安装于方向盘旁侧，以采集车道标线相关的视频素材。该摄像头支持多种分辨率与帧率 (fps) 组合的录制模式，具体包括4K分辨率（帧率60/30fps）以及1080p/720p分辨率（帧率30/60/240fps）。本次采集采用1080p分辨率、30fps的录制模式，随后将采集所得视频转换为1920×1080分辨率的图像帧，再将所有图像帧统一调整至224×224分辨率，以适配该框架的输入要求。 本数据集共分为三大类别，分别为车道标线模式 (lane markings pattern)、光照变化 (illumination variation) 与自然气候 (natural climate)。其中车道标线模式类别包含7900帧图像，涵盖实线车道、双车道标线、弯道车道以及车辆障碍物四类场景；光照变化类别包含5000帧图像，涵盖弱光、暗光以及阴天三种光照条件；自然气候类别则包含约2500帧雨天场景图像帧。所有图像均采用JPG格式存储。