| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: objects |
| struct: |
| - name: bbox |
| list: |
| list: float64 |
| - name: categories |
| list: |
| class_label: |
| names: |
| '0': tree |
| '1': flower |
| '2': premature |
| '3': unripe |
| '4': ripe |
| '5': spoiled |
| splits: |
| - name: train |
| num_bytes: 436051831 |
| num_examples: 3098 |
| download_size: 447273427 |
| dataset_size: 436051831 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| license: cc-by-4.0 |
| task_categories: |
| - object-detection |
| size_categories: |
| - 1K<n<10K |
| --- |
| # Cashew Detection |
|
|
| A dataset for object detection of cashew flowers and fruits. The dataset contains 3,098 images with 88,364 bounding box annotations across 6 categories. |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{sanya2024coffee, |
| title={Coffee and cashew nut dataset: A dataset for detection, classification, and yield estimation for machine learning applications}, |
| author={Sanya, Rahman and Nabiryo, Ann Lisa and Tusubira, Jeremy Francis and Murindanyi, Sudi and Katumba, Andrew and Nakatumba-Nabende, Joyce}, |
| journal={Data in Brief}, |
| volume={52}, |
| pages={109952}, |
| year={2024}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| Nakatumba-Nabende, Joyce; Katumba, Andrew; Sanya, Rahman; Tusubira, Jeremy; Murindanyi, Sudi; Namanya, Gloria; Nabiryo, Ann (2023), “Coffee and Cashew Nut Dataset”, Mendeley Data, V1, doi: 10.17632/r46c6bpfpf.1 |
|
|
| *This dataset was reformatted from its original format to match HuggingFace standards.* |
