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metadata
dataset_info:
  features:
    - name: image
      dtype: image
    - name: mask
      dtype:
        image:
          mode: L
  splits:
    - name: train
      num_bytes: 1236712550
      num_examples: 670
  download_size: 1236834019
  dataset_size: 1236712550
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: mit
task_categories:
  - image-segmentation
size_categories:
  - n<1K

Apple Segmentation Minnesota

A dataset for semantic segmentation of Apple Segmentation Minnesota. The dataset contains 670 images with pixel-level mask annotations.

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

Citation

@misc{hani2019minneapple,
title={MinneApple: A Benchmark Dataset for Apple Detection and Segmentation},
author={Nicolai Häni and Pravakar Roy and Volkan Isler},
year={2019},
eprint={1909.06441},
archivePrefix={arXiv},
primaryClass={cs.CV}
}

https://rsn.umn.edu/projects/orchard-monitoring/minneapple