| --- |
| 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 |
|
|
| ```bibtex |
| @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 |
