Abstract
This extensive dataset of herbal plants can be highly beneficial for the potential development of agricultural research and practical plant identification tasks. This article introduces a dataset named "BDHerbalPlants" with 1792 raw, high-quality images and 14,336 augmented data images of herbal plants. It contains images of eight distinct herbal plants from different regions, including Dhaka and Tangail. The eight plants are Eclipta prostrata, Ocimum tenuiflorum, Centella asiatica, Mentha arvensis, Kalanchoe pinnata, Azadirachta indica, Coriandrum sativum, Datura stramonium. Each image is carefully captured and labeled after verifying by experts. The significance of this dataset is showcased using popular pre-trained models such as Xception, DenseNet201, and RegNetY032 DL models. This herbal plant data has immense potential to be seamlessly integrated into Deep learning (DL) tasks and play a significant role in the healthcare and pharmaceutical industry. It serves as valuable data for future research for agricultural Informatics and classifying herbal plants that can be found in woods but are challenging to identify without field knowledge.