道路病害数据集

本“道路病害训练数据集”主要依赖于内部数据采集 ，“自行产生”是其核心特征，数据来源于自有或部署的感知设备和处理平台。
AI边缘/云端实时分析： 通过部署在边缘设备或云平台的AI模型，对实时视频流进行逐帧或关键帧分析。
结构化数据提取： AI模型识别并提取视频画面中的道路病害信息，生成结构化数据记录，包括但不限于：病害类型： 坑槽、裂缝（横向、纵向、网状）、不规则沉陷/凸起、修补破损等。

This "Road Damage Training Dataset" primarily relies on internal data collection, with "self-generated" as its core characteristic. The data is sourced from proprietary or deployed sensing equipment and processing platforms.

AI Edge/Cloud Real-Time Analysis: Deploy AI models on edge devices or cloud platforms to conduct frame-by-frame or keyframe analysis on real-time video streams.

Structured Data Extraction: AI models identify and extract road damage information from video frames, generating structured data records including but not limited to the following damage types: Potholes, cracks (transverse, longitudinal, alligator cracks), irregular settlement/protrusion, damaged repair patches, etc.