Contrasted-Fertilization Wheat Ear Dataset 2020
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Overview This dataset contains 701 wheat RGB images in which all the ears have been manually labelled with bounding boxes. Its primary function is to provide training or test data for deep learning models aiming at the detection of wheat ears. In terms of diversity, it integrates wheat images from two varieties, at all the key development stages from heading to maturity, and for four or eight contrasted nitrogen fertilization management. Field experiments and image acquisition Images were acquired during the 2020 season in two trial fields located in the Hesbaye area, Belgium. The images were captured by two RGB cameras in nadir position. Those cameras were positioned on the cantilever beam to avoid shadows from the phenotyping platform. The auto-exposure algorithm was tuned to prevent, as possible, image saturation. All the details regarding the field experiments and the image acquisition can be found in the related paper: "Dandrifosse S., Ennadifi E., Carlier A., Gosselin B., Dumont B. & Mercatoris B., 2022. Deep learning for wheat ear segmentation and ear density measurement : From heading to maturity. Comput. Electron. Agric. 199(June), DOI:10.1016/j.compag.2022.107161." Image pre-processing 2048 x 2560 pixel images were acquired in the field, but each of them was converted to four square sub-images of 1024 x 1024 pixels. The labelled images in this dataset are the sub-images. Ear bounding boxes The dataset contains a total of 77657 bounding boxes stored in csv files as Python-style lists of [xmin, ymin, width, height]
概述：本数据集包含701张小麦RGB图像，所有麦穗均已通过人工方式标注边界框（bounding boxes）。其核心功能为面向麦穗检测任务的深度学习模型提供训练或测试数据。在多样性层面，该数据集涵盖两个小麦品种的样本，覆盖从抽穗期至成熟期的全部关键生育阶段，并设置了4种或8种差异化的氮肥管理处理方案。 田间试验与图像采集：图像采集于2020年生长季，地点位于比利时赫斯贝（Hesbaye）地区的两块试验田。图像由两台处于天底视角（nadir position）的RGB相机采集，相机安装于悬臂梁上以避免表型平台产生的阴影。自动曝光算法经过调校，尽可能防止图像过饱和。有关田间试验与图像采集的全部细节可参阅相关论文："Dandrifosse S., Ennadifi E., Carlier A., Gosselin B., Dumont B. & Mercatoris B., 2022. 深度学习用于麦穗分割与穗密度测量：从抽穗期至成熟期. Comput. Electron. Agric. 199(June), DOI:10.1016/j.compag.2022.107161." 图像预处理：野外采集的原始图像分辨率为2048×2560像素，每张图像均被裁剪为4张1024×1024像素的方形子图像。本数据集提供的标注图像即为上述子图像。 麦穗边界框：本数据集共包含77657个边界框，以Python风格的[xmin, ymin, width, height]列表形式存储于CSV（Comma-Separated Values）文件中。
