Deep features from Pre-trained CNNs and a vision transformer for amazonian timber species recognition using classical machine learning and random image patches

This dataset contains 864 macroscopic transverse-section wood images of six commercially harvested timber species from the Brazilian Amazon: Eschweilera grandiflora, Lecythis chartacea, Lecythis pisonis, Pseudopiptadenia suaveolens, Pouteria ramiflora, and Tachigali myrmecophila. The dataset comprises samples from 24 trees and 72 wood blocks. Macroscopic images were acquired using a Bioptika L60 stereomicroscope at 10× magnification, with image dimensions of 2569 × 1920 pixels. Wood samples were collected from the Forest Management Area of Fazenda Rio Flores I, located in Vitória do Xingu, Pará, Brazil (SIRGAS 2000; 52°13′19.42″ W, 02°52′06.12″ S). The property covers a total area of 286.5913 ha, of which 157.9396 ha corresponds to the Legal Reserve Area. Forest harvesting activities were authorized by the competent environmental agency under Forest Exploitation Authorization (FEA) No. 273936/2021 (SEMAS-PA, 2021). The six timber species were randomly selected for sampling, and access to genetic heritage was registered in CGEN/SISGEN under registration No. A599206. This dataset is associated with the article: Deep features from Pre-trained CNNs and a vision transformer for Amazonian timber species recognition using classical machine learning and random image patches, published in the Journal of the Indian Academy of Wood Science. DOI: 10.1007/s13196-026-00425-5.