LuffaFolio: A Multidimensional Image Dataset of Smooth Luffa.

This article introduces a comprehensive dataset designed for researchers to classify diseases in Luffa leaves, determine the grade of Luffa from Luffa images, and identify different growth stages throughout the year. The dataset is meticulously organized into three sections, each concentrating on specific facets of Luffa Aegyptiaca, commonly known as Smooth Luffa (Dhundol/). These images were captured in various village fields in Faridpur, Bangladesh. The sections include the assessment of Smooth Luffa quality, the identification of plant diseases, and the documentation of Luffa flowers. The dataset is divided into three sections, totaling 1933 original JPG images. The "Luffa Diseases" section features images of smooth Luffa leaves, depicting various diseases and unaffected leaves. Categories in this section encompass Alternaria Disease, Angular Spot Disease, Holed Leaves, Mosaic Virus, and Fresh Leaves, totaling 1228 JPG raw images. The "Flowers" category comprises 362 JPG raw images, showcasing different maturity stages in smooth Luffa flowers. Finally, the "Luffa Grade" section focuses on categorizing smooth Luffa into fresh and defective categories, presenting 343 JPG raw images for this purpose.

BananaSet: A dataset of banana varieties in Bangladesh.

This article introduces a primary dataset sourced from diverse marketplaces in Bangladesh, encompassing six distinct banana varieties predominantly consumed locally. The dataset comprises the following banana types: Shagor, Shabri, Champa, Anaji, Deshi, and Bichi. High-resolution images of bananas from each category were acquired using a smartphone camera. A total of 1166 images were captured but did not maintain a uniform distribution. Only the augmented data has 1000 images per category which is a total of 6000 images. The proposed dataset exhibits substantial potential for impact and utility, offering a range of attributes, including but not limited to the representation of six diverse banana varieties, each possessing unique flavors and holding promise for various applications within the agriculture and food manufacturing industries.