Agarwood Leaf Image Dataset for Pest and Disease Analysis in Real-World Environment
Description
This is part of the entire dataset comprises a total of 5,472 images of agarwood leaves curated and collected 14 classes from Benutan, Bukit Silat, Batong, Brunei Darussalam. Among which, this repo contains 1,071 images of Spider and Webs, Scale Insects, Mealybugs, Flea Beetles, and Brown Clumps in 5 pest classes. Each image has been carefully captured indicate specific regions as either healthy or diseased, given that each image includes a complex natural background. For structured model development, the dataset is divided into five folders each containing distinctive agarwood pests that can be categorized into training, validation and training classes with a 70:15:15 ratio of training, validation and testing, respectively for performance or 80:20 ratio for training and testing, correspondingly. This dataset is particularly valuable for training and validating deep learning and machine learning algorithms aimed at identifying and detecting diseases and pests in agarwood leaves. It offers researchers and learners a robust resource for analysing and improving the health management of agarwood plants through the development of advanced computational models. The rest of the 4,401 images were collected on agarwood diseases in 9 classes, including Downy mildew, Anthracnose, Black spots, Powdery mildew, Translucent lesions, Brown spots, Mosaic Viruses, Sooty mold, and one of which is healthy class can be accessed at: 10.5281/zenodo.14842100.