---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': Akca Pear
          '1': Amasya Apple
          '2': Angeleno Plum
          '3': Austria Everbearing Mulberry
          '4': Avocado
          '5': Bardacik Fig
          '6': Bilecik Walnut
          '7': Black Diamond Plum
          '8': Black Fig
          '9': Black Mulberry
          '10': Black Splendor Plum
          '11': Carob
          '12': Chestnut
          '13': Chocolate Persimmon
          '14': Cornelian Cherry
          '15': Deveci Pear
          '16': Duke Blueberry
          '17': Egrisap Pear
          '18': Ekmek Quince
          '19': Esme Quince
          '20': Feijoa
          '21': Ferragnes Almond
          '22': Fortune Plum
          '23': Fuji Apple
          '24': Golden Apple
          '25': Granny Smith Apple
          '26': Hachiya Persimmon
          '27': Hale Peach
          '28': Hazelnut
          '29': Igdir Apricot
          '30': Jujube
          '31': Kagizman Long Apple
          '32': Kiwi
          '33': Kumquat
          '34': Kutahya Sour Cherry
          '35': Lemon
          '36': Loquat
          '37': Margarita Marilla Pear
          '38': Medlar
          '39': Murdum Plum
          '40': Napolyon Cherry
          '41': Nashi Pear
          '42': Orange
          '43': Papaz Plum
          '44': Patlican Fig
          '45': Pomegranate
          '46': Red Azarol
          '47': Red Haven Peach
          '48': Red Nectarine
          '49': Redlove Apple
          '50': Santa Maria Pear
          '51': Sebin Walnut
          '52': Sekerpare Apricot
          '53': Show Time Plum
          '54': Sour Cherry
          '55': Starking Apple
          '56': Strawberry Tree
          '57': White Mulberry
          '58': White Nectarine
          '59': Wild Strawberry
          '60': Wild Walnut
          '61': Yellow Cherry
          '62': Yellow Peach
          '63': Ziraat 0900 Cherry
  splits:
  - name: train
    num_bytes: 17671829616
    num_examples: 5815
  download_size: 17375871060
  dataset_size: 17671829616
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: cc-by-4.0
task_categories:
- image-classification
size_categories:
- 1K<n<10K
---
# Sapbark 64 Variety Classification

A dataset for variety classification of sapling bark of fruit trees. The dataset contains 5,815 images across 64 classes.  

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

## Citation

```bibtex
@article{alizadeh2025sapbark,
  title={SapBark-64: A dataset of bark images for 64 fruit-tree sapling classes},
  author={Alizadeh, Sayyad and Shamsi, Hamed},
  journal={Data in Brief},
  pages={112354},
  year={2025},
  publisher={Elsevier}
}
```

ALIZADEH, S. (2025). SapBark-64: A dataset of bark images for 64 fruit-tree sapling classes (Version v1.0) [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.17196298

*This dataset was reformatted from its original format to match HuggingFace standards.*