| --- |
| configs: |
| - config_name: default |
| default: true |
| features: |
| - name: image |
| dtype: image |
| - name: objects |
| sequence: |
| - name: bbox |
| list: float32 |
| - name: categories |
| class_label: |
| names: |
| '0': Early-Fruit |
| '1': Mature |
| '2': Premature |
| '3': Ripe |
| license: cc-by-4.0 |
| task_categories: |
| - object-detection |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # Mango Growth Object Detection |
|
|
| A dataset for object detection of Mango Growth. The dataset contains 2,000 images with 3,174 bounding box annotations across 4 categories. |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{kabir2025smartphone, |
| title={Smartphone image dataset for machine learning-based monitoring and analysis of mango growth stages}, |
| author={Kabir, Sayem and Akon, Md Fokrul and Rashid, Mohammad Rifat Ahmmad and Islam, Maheen and Jabid, Taskeed and Islam, Mohammad Manzurul and Ali, Md Sawkat}, |
| journal={Data in Brief}, |
| volume={61}, |
| pages={111780}, |
| year={2025}, |
| publisher={Elsevier} |
| }``` |
|
|
| Kabir, Sayem ; Rashid, Mohammad Rifat Ahmmad (2024), “Image Dataset for Mango Growth Stages Analysis”, Mendeley Data, V1, doi: 10.17632/5snwpzdtzs.1 |
