Home Appliance Screw Stripping Detection Dataset

In the current industrial landscape, the quality of assembly processes is critical, especially regarding the integrity of screws in home appliances. A significant challenge faced by manufacturers is the identification of stripped screws, which can lead to product failures and safety concerns. Existing solutions often rely on manual inspection, which is time-consuming and prone to human error. This dataset aims to address the need for automated detection systems that can reliably identify stripped screws, thereby enhancing assembly quality and reducing defect rates. The data was collected using high-resolution cameras in a controlled factory environment, ensuring consistent lighting and background conditions. Quality control measures included multiple rounds of labeling by trained technicians, consistency checks across different annotators, and final validation by domain experts. The data is organized in JPG format, with each image stored alongside its metadata in a structured directory format.