TextileClass-7: Dataset for Fabric Material Classification

The annotation process included careful manual verification to ensure label consistency and minimize annotation errors. The dataset is organized into class-specific folders and is compatible with common deep learning frameworks such as TensorFlow, PyTorch, and Keras. It can be readily used for supervised image classification tasks, transfer learning, benchmark evaluations, and comparative studies of machine learning and deep learning algorithms.

Researchers may also utilize this dataset for feature extraction, texture analysis, explainable artificial intelligence (XAI), and vision-based textile inspection systems. This dataset provides a valuable benchmark for the textile industry and the research community by enabling the development of automated fabric recognition systems for smart manufacturing, quality inspection, inventory management, e-commerce product categorization, and intelligent textile applications.