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dataset_info:
features:
- name: image
dtype: image
- name: frame_id
dtype: string
- name: frame_number
dtype: string
splits:
- name: train
num_bytes: 664266743
num_examples: 696
download_size: 664299204
dataset_size: 664266743
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc-by-4.0
size_categories:
- n<1K
---
# Grapesnet Single Cluster Depth
This dataset provides real RGB-D imagery of grape clusters in a mixed agricultural environment. Captured using a tripod-mounted smartphone and depth camera system, it offers synchronized color and depth data for natural vineyard conditions to support crop detection research. The dataset contains 696 images with no classification, segmentation, or bounding-box annotations.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{barbole2023grapesnet,
title={GrapesNet: Indian RGB & RGB-D vineyard image datasets for deep learning applications},
author={Barbole, Dhanashree K. and Jadhav, Parul M.},
journal={Data in Brief},
volume={48},
pages={109100},
year={2023},
publisher={Elsevier}
}
```
Barbole, Dhanashree; Jadhav, Parul (2023), “GrapesNet: Indian Grape Clusters RGB & RGB-D Image Datasets”, Mendeley Data, V1, doi: 10.17632/mhzmzd5cwx.1
*This dataset was reformatted from its original format to match HuggingFace standards.*
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