Watermelon Disease Recognition Dataset

(1) Crop diseases significantly impact agricultural productivity and quality, particularly in watermelon cultivation. Traditional disease diagnosis methods are time-consuming and subjective, creating a demand for efficient machine vision-based disease detection models.

(2) We present a comprehensive watermelon dataset, including images of healthy watermelons and those afflicted by Mosaic Virus, Anthracnose, and Downy Mildew Disease. Collected in collaboration with experts on June 25, 2023, from the Regional Horticulture Research Station in Lebukhali, Patuakhali, Bangladesh. This dataset aids in early disease detection.

(3) Watermelons are essential for global food security but face challenges like disease threats and limited farmer training.

(4) Our dataset supports the development of advanced machine vision algorithms for early disease identification. It contains four watermelon classes: Mosaic Virus, Healthy, Anthracnose, and Downy Mildew, with 1155 original images and 5775 augmented images.

(5) The dataset is accessible on the Mendeley repository, facilitating research and empowering farmers to protect watermelon production and agricultural stability.

（1）作物病害对农业产量与品质产生重大影响，尤其是在西瓜栽培中。传统的病害诊断方法耗时且主观性较强，催生了基于高效机器视觉的病害检测模型的迫切需求。
（2）我们提供了一个全面的西瓜数据集，包括健康西瓜及其感染花叶病毒、炭疽病和霜霉病的图像。该数据集于2023年6月25日与来自孟加拉国帕图阿哈利的Lebukhali地区园艺研究所的专家合作收集。本数据集有助于早期病害检测。
（3）西瓜是全球粮食安全的重要组成部分，但面临着疾病威胁和农民培训不足等挑战。
（4）我们的数据集支持高级机器视觉算法的开发，用于早期病害识别。它包含四个西瓜类别：花叶病毒、健康、炭疽病和霜霉病，共包含1155张原始图像和5775张增强图像。
（5）该数据集可在Mendeley仓库中获取，便于研究并赋予农民保护西瓜生产与农业稳定的权力。