---
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

```bibtex
@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