Datasets:

Project-AgML
/

GrapesNet_depth

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

@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.