Dataset of Chenille yarn

This dataset collects samples of different kinds of defective and normal chenille yarn images for the same batch of chenille yarn made of polyester material, aiming to facilitate the task of recognizing and classifying chenille yarn defects in computer vision and machine learning algorithms. This dataset consists of a total of 2500 images of 5 major chenille yarn defects and 2500 normal chenille yarn images, totaling 5000 images. It is captured by an industrial camera in the state of chenille yarn movement. In this case, the surface light source was set on the backside of the chenille yarn.
The purpose of classification aims to differentiate between defective and normal chenille yarns on the premise that the classification of chenille yarn defects is improved as much as possible at the same time, in order to achieve the purpose of factory production monitoring and realizing the smart factory.
In summary, this dataset is a valuable resource for researchers and practitioners for the task of detecting chenille yarn yarn defects in the textile industry.