Datasets:

Project-AgML
/

sorghum_weed_classification

configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc-by-4.0
task_categories:
  - image-classification
size_categories:
  - 1K<n<10K
dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': BroadLeafWeed
            '1': Grass
            '2': Sorghum
  splits:
    - name: train
      num_bytes: 68451901
      num_examples: 4312
  download_size: 67315495
  dataset_size: 68451901

Sorghum Weed Classification

A dataset for weed classification in sorghum fields. The dataset contains 4,312 images across 3 classes: BroadLeafWeed, Grass, Sorghum.
Images per class:

BroadLeafWeed: 1,441
Grass: 1,467
Sorghum: 1,404

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_Classification”, Mendeley Data, V1, doi: 10.17632/4gkcyxjyss.1