Leaf Image Dataset for Disease Detection in Bitter Gourd, Okra, Pumpkin, and Ridge Gourd.
Description
This dataset contains 4,568 real images of vegetable leaf samples collected during the 2025 growing season from agricultural fields in Baroghoria, Chapai Nawabganj, Rajshahi, Bangladesh. It includes four crops: Bitter Gourd, Okra, Pumpkin, and Ridge Gourd. The samples are divided into nine classes with the following counts: Bitter Gourd: Anthracnose (410 raw, 2,025 augmented, 2,435 total), Downy Mildew (472 raw, 2,365 augmented, 2,837 total), Healthy (501 raw, 2,510 augmented, 3,011 total) Okra: Cercospora Leaf Spot (540 raw, 2,700 augmented, 3,240 total), Healthy (542 raw, 2,710 augmented, 3,252 total) Pumpkin: Downy Mildew (512 raw, 2,560 augmented, 3,072 total), Healthy (535 raw, 2,675 augmented, 3,210 total) Ridge Gourd: Downy Mildew (548 raw, 2,740 augmented, 3,288 total), Healthy (508 raw, 2,540 augmented, 3,048 total) Altogether, there are 4,568 raw images and 22,825 augmented images, making a total of 27,393 images. All images were annotated by agricultural experts. To increase dataset variability and improve model generalisation, augmentation techniques such as rotation, shear, zoom, brightness adjustment and horizontal flipping were applied. Purpose The dataset supports the training and evaluation of machine learning models for plant disease classification. It is useful for research in automated crop monitoring, deep learning, and precision agriculture, facilitating early disease detection and reducing crop losses.
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Institutions
- Daffodil International University