Datasets:

Project-AgML
/

rice_grain_variety_classification

configs:
  - config_name: augmented
    data_files:
      - split: train
        path: augmented/train-*
  - config_name: raw
    data_dir: raw
    default: true
license: cc-by-4.0
task_categories:
  - image-classification
size_categories:
  - 10K<n<100K
dataset_info:
  - config_name: augmented
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': Amon
              '1': BR28
              '2': BR29
              '3': Bashful
              '4': Bashmoti
              '5': Chinigura_Polao
              '6': Ganjiya
              '7': Gutisharna
              '8': Jirashail
              '9': Katari_Polao
              '10': Katarivog
              '11': Lal_Aush
              '12': Lal_Binni
              '13': Lal_Biroi
              '14': Najirshail
              '15': Paijam
              '16': Red_Cargo
              '17': Shampakatari
              '18': Shorna5
              '19': Subol_Lota
    splits:
      - name: train
        num_bytes: 568421638
        num_examples: 23650
    download_size: 820286412
    dataset_size: 568421638
  - config_name: raw
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': Amon
              '1': BR28
              '2': BR29
              '3': Bashful
              '4': Bashmoti
              '5': Chinigura_Polao
              '6': Ganjiya
              '7': Gutisharna
              '8': Jirashail
              '9': Katari_Polao
              '10': Katarivog
              '11': Lal_Aush
              '12': Lal_Binni
              '13': Lal_Biroi
              '14': Najirshail
              '15': Paijam
              '16': Red_Cargo
              '17': Shampakatari
              '18': Shorna5
              '19': Subol_Lota
    splits:
      - name: train
        num_bytes: 299500826
        num_examples: 4730
    download_size: 281318144
    dataset_size: 299500826

Rice Grain Variety Classification

A dataset for variety classification of rice grains. The dataset contains raw and augmented versions.
The raw dataset contains 4,730 images.
Images per class:

Amon: 250
BR28: 230
BR29: 233
Bashful: 252
Bashmoti: 230
Chinigura_Polao: 237
Ganjiya: 233
Gutisharna: 256
Jirashail: 231
Katari_Polao: 242
Katarivog: 233
Lal_Aush: 231
Lal_Binni: 232
Lal_Biroi: 231
Najirshail: 231
Paijam: 234
Red_Cargo: 240
Shampakatari: 234
Shorna5: 238
Subol_Lota: 232

The augmented dataset contains 23,650 images.
Images per class:

Amon: 1,250
BR28: 1,150
BR29: 1,165
Bashful: 1,260
Bashmoti: 1,150
Chinigura_Polao: 1,185
Ganjiya: 1,165
Gutisharna: 1,280
Jirashail: 1,155
Katari_Polao: 1,210
Katarivog: 1,165
Lal_Aush: 1,155
Lal_Binni: 1,160
Lal_Biroi: 1,155
Najirshail: 1,155
Paijam: 1,170
Red_Cargo: 1,200
Shampakatari: 1,170
Shorna5: 1,190
Subol_Lota: 1,160

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

Citation

@article{islam2024visual,
  title={A visual dataset for recognition of rice varieties},
  author={Islam, Md Masudul and Himel, Galib Muhammad Shahriar and Uddin, Mohammad Shorif and Moazzam, Md Golam},
  journal={Data in brief},
  volume={54},
  pages={110442},
  year={2024},
  publisher={Elsevier}
}

Islam, Md Masudul; Himel, Galib Muhammad Shahriar; Moazzam, Md. Golam; Uddin, Mohammad Shorif (2024), “Aruzz22.5K: An Image Dataset of Rice Varieties”, Mendeley Data, V4, doi: 10.17632/3mn9843tz2.4