This dataset1 comprises images depicting dry and wet wood veneers. The data could be used to build and train an ML model that can detect defects in wood veneers during manufacturing.
This repo contains the following structure:
- smaller_veneer_log.csv: CSV file for use in loading the data into PerceptiLabs. This file maps each image to a classification number (0 for dry and 1 for wet).
The following shows a partial example of the data stored in data.csv that is used to load the data into PerceptiLabs. The values in the images column indicate the respective classification depicted in each image.
| images | labels |
|---|---|
| Dry/dry_1001.png | 0 |
| Wet/wet_1101.png | 1 |
The following shows example images from the dataset representing dry veneers:
Due to the amount of data, you must download the image files from the original data source.
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1 Dataset Credits: https://ieee-dataport.org/open-access/veneer21. T. Jalonen, F. Laakom, M. Gabbouj and T. Puoskari, "Visual Product Tracking System Using Siamese Neural Networks," in IEEE Access, vol. 9, pp. 76796-76805, 2021, doi: 10.1109/ACCESS.2021.3082934.