基于人工智能的山区公路交通气象灾害视频分析技术及应用图像及标签数据集

本数据集是为“基于人工智能的山区公路交通气象灾害视频分析”项目而构建的图像及标签数据集。数据集内容包含从云南省内高速公路及国省干道监控视频中采集并处理后的图像，以及对这些图像进行的精细化标注。标注信息主要包括天气现象类型（包含：无灾害天气、小雨、中雨、大雨、暴雨、闪电、轻雾、中雾、大雾、浓雾、小雪、中雪、大雪、暴雪、冰雹、沙尘暴、光晕、冰雪路面）（共18类）。数据集图片总张数：5535000，存储容量合计：4.25TB。该数据集旨在为计算机视觉模型的训练、测试与验证提供高质量的数据支撑，以提升对恶劣气象的智能识别与分析能力。

This is an image and annotation dataset constructed for the project titled "Video Analysis of Meteorological Disasters on Mountainous Highway Traffic Based on Artificial Intelligence". The dataset comprises images collected and processed from surveillance videos of expressways and national/provincial trunk highways within Yunnan Province, along with fine-grained annotations for these images. The annotation information primarily covers weather phenomenon types, including 18 categories: non-disastrous weather, light rain, moderate rain, heavy rain, rainstorm, lightning, light fog, moderate fog, heavy fog, dense fog, light snow, moderate snow, heavy snow, blizzard, hail, sandstorm, halo, and ice-snow covered road. The total number of images in the dataset is 5,535,000, with a combined storage capacity of 4.25 TB. This dataset is intended to provide high-quality data support for the training, testing and validation of computer vision models, so as to enhance the intelligent recognition and analysis capabilities for severe meteorological conditions.

搜集汇总

背景与挑战

背景概述

该数据集包含553.5万张山区公路监控图像，专门标注了18类气象灾害类型，用于训练AI模型实现恶劣天气识别。数据集支持交通气象智能监测预警应用，可降低传统传感器成本，提升山区公路安全管理能力。