Coupling Target Detection Dataset

The current industrial sector faces significant challenges in ensuring the quality and reliability of coupling components within power systems. Traditional inspection methods are often time-consuming and prone to human error, leading to inconsistent quality control. Existing solutions lack sufficient datasets for training effective detection models, resulting in limited automation capabilities. This dataset aims to provide a robust resource for developing advanced detection algorithms that improve inspection accuracy and efficiency. The dataset consists of images collected from various industrial environments using high-resolution cameras, ensuring a diverse representation of coupling components. Quality control measures include multiple rounds of annotation and expert review to maintain high accuracy and consistency. The images are stored in JPEG format, with annotations provided in JSON, allowing easy integration with machine learning workflows.