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Project-AgML/GrapesNet_depth

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… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/GrapesNet_depth.

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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.