RSCD: Road Surface Condition Dataset Dataset Description The Road Surface Condition Dataset (RSCD) is a large scale image dataset containing over 1 million images for road surface condition classification. This dataset is designed for training computer vision models to identify and classify various road surface types, moisture conditions, and damage severity levels. Dataset Summary Total Images : ~1,028,000 images Image Format : JPG Use Cases : Road condition monitoring Autonomous driving systems Infrastructure maintenance Weather aware navigation Dataset Structure The dataset is organized into three splits: Training Set Organization The training data is organized into category specific folders: Surface Types : Asphalt Concrete Gravel Mud Moisture Conditions : Dry Wet Water (standing water/puddles) Severity Levels (for asphalt and concrete): Smooth (no damage) Slight (minor damage) Severe (significant damage) Special Conditions : Fresh snow Ice Melted snow Example Categories dry asphalt smooth Dry asphalt with no damage wet concrete severe Wet concrete with severe damage water asphalt slight Asphalt with standing water and slight damage dry gravel Dry gravel road ice Icy road surfa…
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