Door Handle Detection Dataset

In the current industrial landscape, the quality control of door handles is critical yet challenging due to the high variability in manufacturing processes. Existing solutions often rely on manual inspection, which is time-consuming and prone to human error. This dataset aims to address the technical issues related to automated detection and classification of door handles to enhance efficiency and accuracy. The dataset comprises images collected from various production lines, with a focus on different handle designs and assembly scenarios. Data collection involved using high-resolution cameras in controlled environments to ensure consistency. Quality control measures included multiple rounds of annotations by trained personnel and regular audits to maintain label accuracy. The images are stored in JPG format, organized by categories of door handles.