Tomato Leaf Dataset : A dataset for multiclass disease detection and classification

Published: 5 September 2024| Version 1 | DOI: 10.17632/bpfd9cns5g.1
Contributors:
Ahmed Imtiaz, Fahad Bin Islam Swapnil,
,

Description

The “Tomato Leaf Dataset” is astutely organized into seven types, each type representing a particular tomato leaf to streamline get to and examination.The data for tomato leaves were collected from tomato gardens in Dina- jpur, Thakurgaon, and Kushtia. An experienced gardener from Kushtia and workers from other tomato gardens provided important insights about tomato leaves. Over seven days, we captured around 731 pictures of all categories and classified them according to their types. Number of images: 731 Number of classes: 7 Name if the classes: 1. Category Early Blight 2. Category Black Spot 3. Category Late Blight 4. Category Leaf Mold 5. Category Bacterial Spot 6. Category Target Spot 7. Category Healthy Number of annotation images : 1621 Annotation format: TXT

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Institutions

American International University Bangladesh

Categories

Agricultural Science, Image Processing, Agricultural Engineering, Machine Learning, Tomato, Deep Learning

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