Soybean images dataset for caterpillar and Diabrotica speciosa pest detection and classification
Maria Eloisa Mignoni, Aislan Honorato, Rafael Kunst, Rodrigo da Rosa Righi, Angélica Massuquetti
Abstract
This article presents a dataset of insect-damaged soybean leaves. The capture of images was carried out on several soy farms, under realistic weather conditions, using two cell phones and a UAV. The dataset consists of 3 (three) folders with a total of 6,410 images. The dataset is divided into three categories: (I) healthy plants, (II) plants affected by caterpillars, and (III) images of plants damaged by Diabrotica speciosa. This dataset allows training and validation of machine learning models to diagnose, recognize, and classify soybeans affected by caterpillars or Diabrotica speciosa. The images can be processed according to the user’s need since only the size was standardized during the pre-processing phase.