Datasets:

Project-AgML
/

mango_growth_detection

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

@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