---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: image_type
    dtype: string
  - name: frame_number
    dtype: string
  - name: timestamp_ms
    dtype: string
  splits:
  - name: train
    num_bytes: 886910106
    num_examples: 847
  download_size: 886943095
  dataset_size: 886910106
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: cc-by-4.0
size_categories:
- n<1K
---
# Grapesnet Depth

This dataset comprises real-world RGB-D imagery captured in a mixed vineyard environment for grape crop detection. Images were collected using tripod-mounted smartphone and depth camera systems, providing synchronized color and depth data from Sonaka grapevine locations in Yelavi, Maharashtra, India. The dataset contains 847 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.*