Jute Disease Image Dataset

This meticulously curated collection of images, encompassing healthy jute plants and those affected by Dieback, Holed, Mosaic, and Stem Soft Rot, provides an invaluable foundational resource for training and evaluating machine learning models. The creation of this dataset directly addresses the crucial data void in jute disease imagery, positioning it as a foundational resource that can accelerate ML research and application in jute agriculture. By making this dataset publicly available, the aim is to empower researchers, developers, and agricultural stakeholders to build and deploy automated diagnostic tools. Such tools can enable timely interventions, significantly mitigating yield losses, enhancing food security, and bolstering the resilience and economic prosperity of the \"Golden Fibre\" industry in Bangladesh and beyond. The dataset comprises 1,390 unique images, meticulously collected and preprocessed, with a uniform resolution of 1024x1024 pixels. It is structured into raw and augmented/train-test split versions, catering to various research and development needs.