Project-AgML/rice_grain_variety_classification

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