Washing Machine Drain Pipe Blockage Visual Detection Dataset

The current industrial sector faces significant challenges in diagnosing and maintaining washing machine drainage systems, with many operators relying on manual inspections that are time-consuming and prone to errors. Existing solutions often fail to accurately detect various types of blockages and their severity, leading to inefficiencies and increased maintenance costs. This dataset aims to provide a comprehensive resource for training models that can automatically identify foreign objects or deformation in drainage pipes, thereby enhancing maintenance protocols. The data collection process involved capturing images of various blockage scenarios using high-resolution cameras in controlled environments, ensuring a wide range of conditions are represented. Quality control measures included multiple rounds of annotation by experts, consistency checks to validate labeling accuracy, and expert reviews to ensure high-quality data. The images are stored in JPG format and organized systematically by unique identifiers, ensuring easy retrieval and processing.