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  • A Large Dataset and Benchmarks for Semantic Image Interpretation in the Agricultural Domain. Please find more information at: https://www.phenobench.org/

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    Images captured by a UGV in Eshikon 2016. We labelled the images with pixel-wise semantic segmentation. Please read the README.md before using the data.

  • Images captured by an UAV at Zurich with additional annotations of crops and weeds (2017). The *split.yaml* file contains information about which images belong to the train, val, and test set.

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    This is a template for a data record that is described with a minimum of details. DO NOT USE THESE RECORD FOR ANY RESEARCH.

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    Images captured by a UGV in Ancona 2018. We labelled the images with pixel-wise semantic segmentation. Please read the README.txt before using the data.

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    Images captured by a UGV in Bonn 2017. We also labelled the images with pixel-wise semantic segmentation. Refer to README.txt for more metadata. This data is an extension of the Sugar Beets Dataset, linked here https://www.ipb.uni-bonn.de/data/sugarbeets2016/. For more details, refer here: https://bonndoc.ulb.uni-bonn.de/xmlui/handle/20.500.11811/8981.

  • Images captured by an UAV at Bonn with additional annotations of crops and weeds (2017). The *split.yaml* file contains information about which images belong to the train, val, and test set.

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    This is the Sugar Beets Dataset, linked here https://www.ipb.uni-bonn.de/data/sugarbeets2016/. This dataset contains over 13,000 images captured by a UGV in Bonn 2016. We labelled all the images with pixel-wise semantic segmentation differenting crops and weeds. Corresponding NIR images are also available. Please read the README.md before using the data.