Omkar2118/datasets huggingface dataset:
Hazards&Robots
Full name: Hazards&Robots: A Dataset for Visual Anomaly Detection in Robotics

We consider the problem of detecting, in the visual sensing data stream of an autonomous mobile robot, semantic patterns that are unusual (i.e., anomalous) with respect to the robot’s previous experience in similar environments. These anomalies might indicate unforeseen hazards and, in scenarios where failure is costly, can be used to trigger an avoidance behavior. We contribute three novel image-based datasets acquired in robot exploration scenarios, comprising a total of more than 200k labeled frames, spanning various types of anomalies.

Introducing paper: An Outlier Exposure Approach to Improve Visual Anomaly Detection Performance for Mobile Robots