Indonesia is enriched and guarded with various plants. This plant is useful in many ways in the field of health such as medicinal formulations, the production of herbal products, and medicines to cure many diseases. The traditional Indian medicine system is widely accepted even to this day. India is a rich country to be a habitat for various medicinal plants. Many parts of the plant such as leaves, bark, roots, seeds, fruits, and many more are used as ingredients for the production of herbal remedies. Herbal remedies are preferred in developing and developed countries as an alternative medicine mainly because there are no side effects on the body. Studies reveal that to build intelligent systems for medicinal herb recognition requires a decent plant leaf dataset size. The dataset consists of two species of herbal leaves such as Citrus hystrix and Carica papaya. The dataset consists of 100 images of two species of herbal leaves. Each species consists of 50 high-quality images. Folders are named after scientific names. The picked leaves come from different plants of the same species available around the house. Healthy and mature leaves are selected for the dataset. The tools used are mobile cameras (Model: Asus Zenfone M2 Max for Carica Papaya and iphone Xr for Citrus hystrix). The leaf images in the dataset are arranged in such a fitting position to take pictures clearly in training each machine learning and deep learning model. By releasing this dataset to the public, we hope to stimulate research on medicinal plants where the current lack of public datasets is one of the major obstacles to progress.

THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOVE