Dataset of Deglet Nour date palm bunches for smart harvesting

Abstract

This article introduces a comprehensive dataset designed to facilitate smart harvesting applications for Deglet Nour date palms, focusing on two primary computer vision tasks: branch detection and optimal cutting point localization. Collected from various oases within the Kebili governorate of southern Tunisia during the peak harvesting season of 2023, the dataset consists of 5530 images annotated for object detection and 387 images precisely annotated with keypoints. Captured using a combination of DSLR and smartphone cameras, the dataset captures real- world agricultural complexities, including varied lighting conditions and occlusions, which were covered and uncorvered date bunches. Annotations, performed manually using Roboflow, are provided in widely used YOLO and COCO formats to ensure compatibility and facilitate widespread adoption. By offering structured, high quality annotated images, this dataset supports the robust development, training, and evaluation of advanced computer vision and robotic harvesting systems for precision agriculture.