Datasets:

Project-AgML
/

grape_detection_syntheticday

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

@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}
}