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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
```bibtex
@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.*
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