Shrink Tubing Dataset

Shrink tubing is a commonly used material for protecting and insulating electrical wires, cables, and components in a variety of industries. However, defects and damages in shrink tubing can lead to serious safety and performance issues, making quality control a critical process in manufacturing and maintenance. In this paper, we propose a new dataset of shrink tubing images containing various types of defects and damages, which can be used for training and evaluating machine learning-based quality control systems. The dataset consists of high-resolution images of shrink tubing samples, including both healthy (good) and defective ones. The defects and damages in the images include cuts, tears, and holes. The images were captured using a high-quality camera under various lighting and background conditions, with a variety of angles and orientations.