Supporting data for Deep Learning and Machine Vision based approaches for automated wood defect detection and quality control.

The dataset contains more than 43 000 labeled wood surface defects and covers overall ten types of the most common defects, including live knots, dead knots, knots with crack, cracks, resins, marrows, quartzity, missing knots, blue stain, and overgrown. Each image in the dataset is provided with a semantic map and a bounding box label that allows performing semantic segmentation as well as localization tasks. All data were collected directly from a wood production line during the manufacturing process.