---
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: 78896899
    num_examples: 967
  download_size: 78890411
  dataset_size: 78896899
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---
# Apple Detection Spain

A dataset for object detection of apples. The dataset contains 967 images with 13,835 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{GENEMOLA2019104289,
title = {KFuji RGB-DS database: Fuji apple multi-modal images for fruit detection with color, depth and range-corrected IR data},
journal = {Data in Brief},
volume = {25},
pages = {104289},
year = {2019},
issn = {2352-3409},
doi = {https://doi.org/10.1016/j.dib.2019.104289},
url = {https://www.sciencedirect.com/science/article/pii/S2352340919306432},
author = {Jordi Gené-Mola and Verónica Vilaplana and Joan R. Rosell-Polo and Josep-Ramon Morros and Javier Ruiz-Hidalgo and Eduard Gregorio}
}
```

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