Rose Defect Identification Dataset (RDID)

Roses are among the most cherished ornamental plants worldwide, and their health is crucial for both commercial cultivation and aesthetic value. This dataset focuses on developing an efficient and accurate system for detecting diseases in rose. This dataset is ideal for machine learning tasks involving image classification, recognition, and other computer vision applications. Dataset was collected through field visits to Golaap Gram and Nursery around Daffodil International University. This dataset presents 1,038 Original Rose image where, Healthy rose: 523 and Defect rose: 515. Also add Augmented data where include total 2901 images where, Test: 436 images Train: 2030 images Val: 435 images.