Connector Detection Dataset

The current industrial sector faces significant challenges in ensuring the quality and accuracy of connector assemblies, which are critical for system reliability. Existing solutions often lack precision and are not versatile enough to adapt to various connector types. This dataset aims to address the need for a robust training resource that can improve the performance of detection algorithms in identifying connectors and ensuring proper alignments in automated systems. The dataset consists of images captured in controlled environments using high-resolution cameras, ensuring clarity and detail. Quality control measures include multi-round annotations, consistency checks among annotators, and expert reviews to maintain high standards. Data is organized in a structured manner, with images stored in JPG format and accompanied by metadata for each image in a JSON file.