Bangladesh's economy is primarily driven by the agriculture sector. Rice is one of the staple food of Bangladesh. The count of panicles per unit area serves as a widely used in-dicator for estimating rice yield, facilitating breeding efforts, and conducting phenotypic analysis. By calculating the num -ber of panicles within a given area, researchers and farmers can assess crop density, plant health, and prospective pro-duction. The conventional method of estimating rice yields in Bangladesh is time-consuming, inaccurate, and inefficient. To address the challenge of detecting rice panicles, this arti-cle provides a comprehensive dataset of annotated rice pan-icle images from Bangladesh. Data collection was done by a drone equipped with a 4 K resolution camera, and it took place on April 25, 2023, in Bonkhoria Gazipur, Bangladesh. During the day, the drone captured the rice field from var-ious heights and perspectives. After employing various im-age processing techniques for curation and annotation, the dataset was generated using images extracted from drone video clips, which were then annotated with information re-garding rice panicles. The dataset is the largest publicly ac-cessible collection of rice panicle images from Bangladesh, consisting of 2193 original images and 5701 augmented im-ages.(c) 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )