WalnutData: A UAV Remote Sensing Dataset of Green Walnuts and Model Evaluation

TL;DR

WalnutData is a large-scale UAV-based dataset for green walnut detection under various lighting and occlusion conditions, supporting algorithm development in agricultural computer vision.

Contribution

This paper introduces WalnutData, the first comprehensive UAV remote sensing dataset for green walnuts, with detailed annotations and baseline algorithm evaluations.

Findings

The dataset contains 30,240 images and 706,208 instances.

Baseline evaluations establish standard performance metrics.

The dataset covers diverse lighting and occlusion scenarios.

Abstract

The UAV technology is gradually maturing and can provide extremely powerful support for smart agriculture and precise monitoring. Currently, there is no dataset related to green walnuts in the field of agricultural computer vision. Thus, in order to promote the algorithm design in the field of agricultural computer vision, we used UAV to collect remote-sensing data from 8 walnut sample plots. Considering that green walnuts are subject to various lighting conditions and occlusion, we constructed a large-scale dataset with a higher-granularity of target features - WalnutData. This dataset contains a total of 30,240 images and 706,208 instances, and there are 4 target categories: being illuminated by frontal light and unoccluded (A1), being backlit and unoccluded (A2), being illuminated by frontal light and occluded (B1), and being backlit and occluded (B2). Subsequently, we evaluated many mainstream algorithms on WalnutData and used these evaluation results as the baseline standard. The dataset and all evaluation results can be obtained at https://github.com/1wuming/WalnutData.