| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': black_nightshade |
| '1': cotton |
| '2': tomato |
| '3': velvet_leaf |
| splits: |
| - name: train |
| num_bytes: 2577776587 |
| num_examples: 508 |
| download_size: 2577827161 |
| dataset_size: 2577776587 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| license: mit |
| task_categories: |
| - image-classification |
| size_categories: |
| - n<1K |
| --- |
| # Crop Weeds Greece |
|
|
| A dataset for image classification of Crop Weeds Greece. The dataset contains 508 images across 4 classes: black_nightshade, cotton, tomato, velvet_leaf. |
| Images per class: |
| - black_nightshade: 123 |
| - cotton: 54 |
| - tomato: 201 |
| - velvet_leaf: 130 |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{ESPEJOGARCIA2020105306, |
| title = {Towards weeds identification assistance through transfer learning}, |
| journal = {Computers and Electronics in Agriculture}, |
| volume = {171}, |
| pages = {105306}, |
| year = {2020}, |
| issn = {0168-1699}, |
| doi = {https://doi.org/10.1016/j.compag.2020.105306}, |
| url = {https://www.sciencedirect.com/science/article/pii/S0168169919319854}, |
| author = {Borja Espejo-Garcia and Nikos Mylonas and Loukas Athanasakos and Spyros Fountas and Ioannis Vasilakoglou} |
| } |
| ``` |
|
|
| https://github.com/AUAgroup/early-crop-weed |
