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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': apple
- name: category_names
list: string
splits:
- name: train
num_bytes: 13559242
num_examples: 689
download_size: 13564302
dataset_size: 13559242
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Apple Detection Drone Brazil
A dataset for object detection of apples. The dataset contains 689 images with 2,471 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
@article{DBLP:journals/corr/abs-2110-12331,
author={Thiago T. Santos and Luciano Gebler},
title={A methodology for detection and localization of fruits in apples orchards from aerial images},
journal={CoRR},
volume={abs/2110.12331},
year={2021},
url={https://arxiv.org/abs/2110.12331},
eprinttype={arXiv},
eprint={2110.12331},
timestamp={Thu, 28 Oct 2021 15:25:31 +0200},
biburl={https://dblp.org/rec/journals/corr/abs-2110-12331.bib},
bibsource={dblp computer science bibliography, https://dblp.org}
}
```
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