Global Wheat Head Detection (GWHD) dataset: a large and diverse dataset of high resolution RGB labelled images to develop and benchmark wheat head detection methods

TL;DR

The paper introduces the GWHD dataset, a large, diverse collection of high-resolution RGB images with labeled wheat heads, designed to facilitate the development and benchmarking of wheat head detection methods amid varied observational conditions.

Contribution

It provides a comprehensive, well-annotated dataset for wheat head detection, including guidelines for image acquisition and labeling, supporting reproducibility and benchmarking in the field.

Findings

Contains 4,700 high-resolution RGB images with 190,000 labeled wheat heads.

Includes diverse images from multiple countries and growth stages.

Aims to improve and benchmark wheat head detection methods.

Abstract

Detection of wheat heads is an important task allowing to estimate pertinent traits including head population density and head characteristics such as sanitary state, size, maturity stage and the presence of awns. Several studies developed methods for wheat head detection from high-resolution RGB imagery. They are based on computer vision and machine learning and are generally calibrated and validated on limited datasets. However, variability in observational conditions, genotypic differences, development stages, head orientation represents a challenge in computer vision. Further, possible blurring due to motion or wind and overlap between heads for dense populations make this task even more complex. Through a joint international collaborative effort, we have built a large, diverse and well-labelled dataset, the Global Wheat Head detection (GWHD) dataset. It contains 4,700 high-resolution RGB images and 190,000 labelled wheat heads collected from several countries around the world at different growth stages with a wide range of genotypes. Guidelines for image acquisition, associating minimum metadata to respect FAIR principles and consistent head labelling methods are proposed when developing new head detection datasets. The GWHD is publicly available at http://www.global-wheat.com/ and aimed at developing and benchmarking methods for wheat head detection.