Guava Fruit Disease Dataset

Published: 4 November 2024| Version 1 | DOI: 10.17632/bkdkc4n835.1
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Description

Guava (Psidium guajava) is a vital crop in Bangladesh and South Asia. It is rich in vitamin C, fiber, and other nutrients. However, guava production is declining due to disease. Early detection of infections is essential to protect the harvest. With the rise of expert systems, automatic disease detection can mitigate these losses. This dataset focuses on guava fruit, providing images categorized into three classes: Anthracnose, Fruit Flies, and Healthy fruits. The images, collected from orchards in Rajshahi and Pabna, Bangladesh, were captured in July when fruits were ripening and were most prone to disease. The images were then verified by a plant pathologist. The dataset is intended to support research in image processing and machine learning, aiming to develop systems for early disease detection. Such systems can significantly reduce economic losses and improve guava yields. The dataset includes 473 images of guava fruits. The original photos vary in size and format. Each was preprocessed to 512 x 512 pixels for consistency. Image Information: - Dimensions: 512 x 512 pixels - Color Mode: RGB - Format: PNG - File Size: 300 - 500 KB The dataset covers three main classes: Anthracnose, Fruit Flies, and Healthy fruits. These are common conditions in guava farming. Images underwent preprocessing steps such as unsharp masking and CLAHE. The preprocessed images are augmented to increase in number to 3,784 image data. The following tree shows the distribution of images across three subsets: Dataset │ ├── train (2,647 images) │ ├── Anthracnose │ ├── Fruit Flies │ └── Healthy fruits │ ├── test (382 images) │ ├── Anthracnose │ ├── Fruit Flies │ └── Healthy fruits │ └── val (775 images) ├── Anthracnose ├── Fruit Flies └── Healthy fruits

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Institutions

Hajee Mohammad Danesh Science and Technology University

Categories

Computer Vision, Image Processing, Image Enhancement

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