UDCAD-DFL-DL: A unique dataset for classifying and detecting agricultural diseases in dragon fruits and leaves
Pronob Chandra Sarkar1, Gourab Kumar Pranta1, Mayen Uddin Mojumdar1
1Multidisciplinary Action Research Laboratory, Department of Computer Science and Engineering, Daffodil International University, Birulia, Dhaka 1216, Bangladesh.
Abstract:
Leaf and fruit diseases are unavoidable due to the unpredictability of climate variability and environmental changes. This study presents dragon fruit and leaf diseases dataset. The dataset includes a total of 4,518 clear and detailed images. The dataset lists the following diseases of leaf and fruit along with the number of images for each: Bacterial Diseases (498), Fungal Infections (Anthracnose or Stem Canker) (84), Healthy Leaves (2,242), Sunburn Damage (271), Healthy Fruits (333), Insect Infected Fruits (53), Mealybugs and Scale Insects (Fruits) (173), Bacterial Wilt (Fruits) (84). All images were captured with two smartphones one is Google Pixel 7 Pro and another one is iPhone 14 Pro in the Dhaka Division. This dataset focuses on analysing the diseases of Dragon leaf and fruit to improving the agriculture sector.
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