Autonomous vehicles are growing rapidly, in well-developed nations like America, Europe, and China. Tech giants like Google, Tesla, Audi, BMW, and Mercedes are building highly efficient self-driving vehicles. However, the technology is still not mainstream for developing nations like India, Thailand, Africa, etc., In this paper, we present a thorough comparison of the existing datasets based on well-developed nations as well as Indian roads. We then developed a new dataset "Indian Roads Dataset" (IRD) having more than 8000 annotations extracted from 3000+ images shot using a 64 (megapixel) camera. All the annotations are manually labelled adhering to the strict rules of annotations. Real-time video sequences have been captured from two different cities in India namely New Delhi and Chandigarh during the day and night-light conditions. Our dataset exceeds previous Indian traffic light datasets in size, annotations, and variance. We prove the amelioration of our dataset by providing an extensive comparison with existing Indian datasets. Various dataset criteria like size, capturing device, a number of cities, and variations of traffic light orientations are considered. The dataset can be downloaded from here https://sites.google.com/view/ird-dataset/home
翻译:例如谷歌、特斯拉、奥迪、宝马、奔驰等技术巨头正在建造高效的自驾驶车辆。然而,印度、泰国、非洲等发展中国家尚未将这种技术纳入主流。 本文对基于发达国家和印度道路的现有数据集进行了彻底比较。然后我们开发了一套新的数据集“印度公路数据集 ” (IRD ), 该数据集有8000多份说明来自3000+图像,使用64(Megapixel)相机拍摄。所有说明都手工贴上符合严格的说明规则的标签。印度的两个不同城市,即新德里和昌迪加尔的实时视频序列在白天和夜光条件下被拍摄。我们的数据集在大小、说明和差异方面超过了以前的印度交通灯数据集。我们通过提供与现有印度数据集的广泛比较,证明了我们数据集的改善。各种数据设置标准,如大小、摄取设备、城市数量、城市/城市流量方向等等,这里可以进行下载。 数据设置/浏览/浏览。