---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: objects
    struct:
    - name: bbox
      list:
        list: int64
    - name: categories
      list:
        class_label:
          names:
            '0': grape
            '1': '1'
  splits:
  - name: train
    num_bytes: 48707920
    num_examples: 448
  download_size: 48689074
  dataset_size: 48707920
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---
# Grape Detection Syntheticday

A dataset for object detection of synthetic grape bunches. The dataset contains 448 images with 8,828 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{10.3389/fpls.2019.01185,
AUTHOR={Bailey, Brian N.},
TITLE={Helios: A Scalable 3D Plant and Environmental Biophysical Modeling Framework},
JOURNAL={Frontiers in Plant Science},
VOLUME={10},
YEAR={2019},
URL={https://www.frontiersin.org/article/10.3389/fpls.2019.01185},
DOI={10.3389/fpls.2019.01185},
ISSN={1664-462X}
}
```