Datasets:

Project-AgML
/

sorghum_weed_segmentation

configs:
  - config_name: default
    default: true
    features:
      - name: image
        dtype: image
      - name: annotation
        dtype:
          image:
            mode: L
license: cc-by-4.0
task_categories:
  - image-segmentation
size_categories:
  - n<1K

Sorghum Weed Segmentation

A dataset for semantic segmentation of weeds in a sorghum plot. The dataset contains 252 images with pixel-level mask annotations. In the masks, 0 is the background, 1 is sorghum, 2 is grass, and 3 is broadleaf weed.

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

Citation

@article{justina2024sorghumweeddataset_classification,
  title={SorghumWeedDataset\_Classification and SorghumWeedDataset\_Segmentation datasets for classification, detection, and segmentation in deep learning},
  author={Justina, Michael J and Thenmozhi, M},
  journal={Data in brief},
  volume={52},
  pages={109935},
  year={2024},
  publisher={Elsevier}
}

Michael, Justina; M, Thenmozhi (2023), “SorghumWeedDataset_Segmentation”, Mendeley Data, V1, doi: 10.17632/y9bmtf4xmr.1