VegNet: An extensive dataset of cauliflower images to recognize the diseases using machine learning and deep learning models

Published: 29 April 2022| Version 3 | DOI: 10.17632/t5sssfgn2v.3
Aditya Rajbongshi,


(1) The world economy largely depends on vegetable production, whereas Cauliflower is an extremely healthy vegetable that’s a significant source of nutrients. It also contains unique plant compounds that may reduce the risk of several diseases, including heart disease and cancer. Because of the early disease recognition of cauliflower, the farmer cannot produce high yield and face economic loss. (2) In the recent era, image classification and detection is crucial application of Computer Vision. (3) In this dataset, two types files of cauliflower images are included, namely the original image file and the augmented image file. Three types of diseases, namely downy mildew, black rot, and bacterial spot rot, exist in every file. Besides, the disease free image of a cauliflower is also included. (4) A total of six hundred and fifty six images (656) are collected from the sunflower garden contained in the original image file. Then the augmentation operation is performed to boost the images, and a total of seven thousands and three hundred sixty (7360) images are contained in the augmented image file. (5) The images of cauliflower (disease-affected and disease-free) are assembled from the Manikganj (vegetable producing zone nearby the capital city of Dhaka) area of Bangladesh.



National Institute of Textile Engineering and Research


Machine Learning, Feature Extraction, Image Classification, Convolutional Neural Network, Deep Learning