Datasets:
dataset_info:
- config_name: augmented
features:
- name: image
dtype: image
- name: mask
dtype: image
- name: split
dtype: string
- name: source
dtype: string
- name: plot
dtype: string
splits:
- name: train
num_bytes: 219439737
num_examples: 3859
download_size: 316352696
dataset_size: 219439737
- config_name: raw
features:
- name: image
dtype: image
- name: mask
dtype: image
- name: source
dtype: string
- name: plot
dtype: string
splits:
- name: train
num_bytes: 91246792
num_examples: 919
download_size: 91381170
dataset_size: 91246792
configs:
- config_name: augmented
data_files:
- split: train
path: augmented/train-*
- config_name: raw
data_files:
- split: train
path: raw/train-*
default: true
license: cc-by-4.0
task_categories:
- image-segmentation
size_categories:
- n<1K
Openear Base Segmentation
This dataset provides real-world RGB imagery of maize crops in field environments, captured at Hongqi Base, Hainan, China. Collected using ground-based platforms with a Raspberry Pi HQ camera during the 2025-2026 growing season, it supports semantic segmentation tasks for agricultural phenotyping in maize fields. The dataset contains raw and augmented versions. The raw split contains 919 images with pixel-level mask annotations.
The augmented split contains 3,859 images with pixel-level mask annotations.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
The original train/test/val split has been preserved in the split column.
Citation
@article{fan2026openear,
title={OpenEar: an ultra-affordable, high-throughput, and accurate maize ear phenotyping system},
author={Fan, Shaoqi and Li, Guoji and Bahitwa, Revocatus and Jia, Zhiguo and Zhang, Hongwei and Shao, Jinghong and Yu, Qiuying and Chen, Xiaoran and Qian, Yiheng and Xu, Mingchi and Zhu, Linlin and Wang, Hai},
journal={Plant Methods},
volume={22},
pages={26},
year={2026},
publisher={BioMed Central}
}
Fan, S. (2025). Datasets for OpenEar model training (Version 2). figshare. https://doi.org/10.6084/m9.figshare.26282563.v2
This dataset was reformatted from its original format to match HuggingFace standards.