PRMI Dataset
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The PRMI: Plant Root Minirhizotron Imagery dataset features over 72,000 RGB root images, encompassing six distinct plant species: cotton, papaya, peanut, sesame, sunflower, and switchgrass. These images cover a wide range of conditions, including varying root ages, structures, soil types, and depths beneath the soil surface. All images come with image-level labels indicating the presence or absence of roots, facilitating weakly supervised learning for root segmentation tasks. Additionally, more than 63,000 images have been manually annotated with pixel-level binary masks, serving as ground truth data for supervised learning in semantic segmentation tasks. The primary objective of introducing this dataset is to streamline the automatic segmentation of plant roots and advance RSA research through deep learning and other image analysis techniques.
PRMI(植物根微细根管图像)数据集包含超过72,000张RGB根图像,涵盖了包括棉花、木瓜、花生、芝麻、向日葵和草地六种不同的植物物种。这些图像涵盖了广泛的条件,包括不同的根龄、结构、土壤类型以及土壤表面以下的深度。所有图像均附有图像级标签,指示根的存在与否,便于进行弱监督学习以实现根分割任务。此外,超过63,000张图像已经通过人工标注了像素级二值掩码,作为语义分割任务中监督学习的基准数据。引入本数据集的主要目的是通过深度学习和其他图像分析技术简化植物根的自动分割,并推进根系结构分析(RSA)研究。




