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dataset_info:
features:
- name: image
dtype: image
- name: objects
struct:
- name: bbox
list:
list: int64
- name: categories
list:
class_label:
names:
'0': mango
splits:
- name: train
num_bytes: 78222025
num_examples: 1242
download_size: 77966427
dataset_size: 78222025
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Mango Detection Australia
A dataset for object detection of mangoes. The dataset contains 1,242 images with 10,619 bounding box annotations across 1 category.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@Misc{Koirala2019,
author={Koirala, Anand and Walsh, Kerry and Wang, Z. and McCarthy, C.},
title={MangoYOLO data set},
year={2019},
month={2021},
day={10-19},
publisher={Central Queensland University},
url={https://figshare.com/articles/dataset/MangoYOLO_data_set/13450661, https://researchdata.edu.au/mangoyolo-set}
}
```
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