| dataset_info: | |
| features: | |
| - name: image | |
| dtype: image | |
| - name: objects | |
| struct: | |
| - name: bbox | |
| list: | |
| list: int64 | |
| - name: categories | |
| list: | |
| class_label: | |
| names: | |
| '0': whitefly | |
| - name: abundance_level | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 3641888361 | |
| num_examples: 3000 | |
| download_size: 4121192636 | |
| dataset_size: 3641888361 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| # Cassava Whitefly Detection | |
| This dataset contains real-world RGB images of cassava plants in field conditions from Namulonge, Uganda, focusing on detecting whitefly infestations. Images were captured using a handheld smartphone (Tecno Spark 3) under natural field environments, providing practical examples for agricultural computer vision applications. The dataset contains 3,000 images with 212,951 bounding box annotations across 1 category. | |
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. | |
| ## Citation | |
| ```bibtex | |
| @article{nakatumbanabende2022dataset, | |
| title={A dataset of cassava whitefly count images}, | |
| author={Nakatumba-Nabende, Joyce and Tusubira, Jeremy Francis and Babirye, Claire and Nsumba, Solomon and Abu, Christopher Omongo}, | |
| journal={Data in Brief}, | |
| volume={41}, | |
| pages={107911}, | |
| year={2022}, | |
| publisher={Elsevier} | |
| } | |
| ``` | |
| Tusubira, Jeremy (2022), “Cassava Whitefly Dataset”, Mendeley Data, V3, doi: 10.17632/5g38399z9p.3 | |
| *This dataset was reformatted from its original format to match HuggingFace standards.* | |