Datasets:

Project-AgML
/

maize_nitrogen_deficiency_classification

dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': '0'
            '1': '75'
            '2': '136'
  splits:
    - name: train
      num_bytes: 513958144
      num_examples: 1200
  download_size: 514177576
  dataset_size: 513958144
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

Maize Nitrogen Deficiency Classification

A dataset for image classification of Maize leaves with varying levels of nitrogen deficiency. The dataset contains 1,200 images across 3 classes: 0, 75, 136.
Images per class:

0: 400
75: 400
136: 400

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

Citation

@article{salai2023nitrogen,
  title={Nitrogen deficiency in maize: Annotated image classification dataset},
  author={Salaić, Miroslav and Novoselnik, Filip and Žarko, Ivana Podnar and Galić, Vlatko},
  journal={Data in Brief},
  volume={50},
  pages={109625},
  year={2023},
  publisher={Elsevier}
}

Galic, Vlatko; Podnar Zarko, Ivana; Novoselnik, Filip; Salaic, Miroslav (2023), “Nitrogen deficiency in maize: annotated image classification dataset”, Mendeley Data, V1, doi: 10.17632/g7xnn2bm4g.1

This dataset was reformatted from its original format to match HuggingFace standards.