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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': 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}
}
``` |