---
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}
}
```