Stomata hub hosts published datasets to support the creation of deep learning architectures for the analysis of stomata. We hope this will continue to grow as researchers from other institutions reach out to provide their own datasets and form collaborations. The existing datasets hosted here come with annotations ranging from simple points through to detailed segmentation masks. Each is aimed at providing valuable training and testing data for machine learning and computer vision applications, including classification, object localisation, and segmentation. If you have a dataset you would like to share or have any questions about existing datasets please do get in touch here.
All available datasets have been shared with the permission of the authors. Please ensure you include original citations in your work. Those that are currently unavailable are either still waiting permission from the original authors, or have had the request for permission to share rejected.
Please note: All hosted datasets have been pre-processed using Contrast Limited Adaptive Histogram Equalisation (CLAHE) to remove colour biases and improve the contrast, and a conversion of annotation files to a generic xml format, again supporting more generic applications. More details on the format can be found here. If you require the annotations converting to a different format, please get in touch and we can arrange to convert these.