| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: objects |
| struct: |
| - name: bbox |
| list: |
| list: float64 |
| - name: categories |
| list: |
| class_label: |
| names: |
| '0': bud |
| '1': flower |
| '2': early-fruit |
| '3': mid-growth |
| '4': mature |
| splits: |
| - name: train |
| num_bytes: 887034006 |
| num_examples: 5857 |
| download_size: 832778925 |
| dataset_size: 887034006 |
| 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 |
| --- |
| |
| # Pomegranate Growth Detection |
|
|
| A dataset for object detection of Pomegranates as they grow. The dataset contains 5,857 images with 11,484 bounding box annotations across 5 categories. |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{zhao2023dataset, |
| title={A dataset of pomegranate growth stages for machine learning-based monitoring and analysis}, |
| author={Zhao, Jifei and Almodfer, Rolla and Wu, Xiaoying and Wang, Xinfa}, |
| journal={Data in brief}, |
| volume={50}, |
| pages={109468}, |
| year={2023}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| Zhao, Jifei; Almodfer, Rolla (2023), “Pomegranate Images Dataset”, Mendeley Data, V5, doi: 10.17632/kgwsthf2w6.5 |
