| --- |
| configs: |
| - config_name: raw |
| default: true |
| data_dir: raw |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': Bad |
| '1': Good |
| - config_name: augmented |
| data_dir: augmented |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': Bad |
| '1': Good |
| license: cc-by-4.0 |
| task_categories: |
| - image-classification |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| # Efficientmaize Classification |
|
|
| A dataset for quality classification of maize. The dataset contains raw and augmented versions. |
| The raw dataset contains 4,846 images. |
| Images per class: |
| - Bad: 2,211 |
| - Good: 2,635 |
|
|
| The augmented dataset contains 28,899 images. |
| Images per class: |
| - Bad: 13,246 |
| - Good: 15,653 |
|
|
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{asante2024efficientmaize, |
| title={EfficientMaize: A lightweight dataset for maize classification on resource-constrained devices}, |
| author={Asante, Emmanuel and Appiah, Obed and Appiahene, Peter and Adu, Kwabena}, |
| journal={Data in Brief}, |
| volume={54}, |
| pages={110261}, |
| year={2024}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| Asante, Emmanuel ; Appiah, Obed; APPIAHENE, PETER (2023), “Lightweight Dataset for Maize Classification on Resource-Constrained Devices”, Mendeley Data, V2, doi: 10.17632/r6vvm5jkh6.2 |
