Datasets:

Project-AgML
/

Alphonso_Mango_phenotyping

dataset_info:
  features:
    - name: image
      dtype: image
    - name: sample_id
      dtype: string
    - name: fruit diameter (mm)
      dtype: float64
    - name: width across schoulder (mm)
      dtype: float64
    - name: Actual Weight (gms)
      dtype: float64
  splits:
    - name: train
      num_bytes: 32507327
      num_examples: 100
  download_size: 32511024
  dataset_size: 32507327
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc-by-4.0
task_categories:
  - other
size_categories:
  - n<1K

Alphonso Mango Phenotyping

This dataset comprises RGB images of Alphonso mango fruits captured in a controlled laboratory environment in Mysuru, India. Images were collected using a fixed-position Logitech C270 webcam during the May/June 2022 phenotyping period, providing standardized visual data for agricultural phenotyping research. The dataset contains 100 images, each paired with the following ground-truth measurement(s): Actual Weight (gms), fruit diameter (mm), width across schoulder (mm).

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

Citation

@article{prabhu2023amdpwe,
  title={AMDPWE: Alphonso Mango Dataset for Precision Weight Estimation},
  author={Prabhu, Akshatha and Rani, N. Shobha},
  journal={Data in Brief},
  volume={51},
  pages={109778},
  year={2023},
  publisher={Elsevier}
}

Prabhu, Akshatha; Rani, N.Shobha (2023), “Alphonso Mangoes Image Dataset”, Mendeley Data, V1, doi: 10.17632/8sjny373pz.1

This dataset was reformatted from its original format to match HuggingFace standards.