Rainy Weather In-Car Driving Perspective Dataset

The current transportation industry faces numerous challenges in autonomous driving under rainy conditions, such as reduced visibility and slippery roads, resulting in decreased target detection accuracy. Existing solutions are mostly concentrated on sunny data, lacking rain-specific scene data, leading to insufficient model adaptability in rainy environments. This dataset aims to provide abundant rainy weather in-car driving perspective images to help improve the recognition capability of autonomous driving systems in complex weather conditions. Data collection is performed using high-definition cameras in rainy environments across different cities to ensure diverse traffic scenes coverage. The data has undergone multiple rounds of annotation, utilizing consistency checks and expert review to ensure annotation quality. The data is stored in JPG format, with each image accompanied by multiple annotation fields to facilitate subsequent processing and analysis. The dataset contains a total of 5000 images, with a total file size of approximately 1.2G.