---
license: mit
task_categories:
- image-classification
tags:
- biology
---

# Dataset Card for Ultra-FGVC

## Dataset Summary
Ultra-FGVC (Ultra-Fine-Grained Visual Categorization) is a benchmark dataset designed for ultra-fine-grained image classification tasks, particularly in biological domains such as plant phenotype analysis. It consists of several subsets featuring subtle inter-class visual differences. This dataset was originally proposed in the ICCV 2021 paper.

This Hugging Face version mirrors the original dataset and is provided for convenience and research reproducibility.

| Datasets  | # of Categories | Training | Test   |
| --------- | --------------- | -------- | ------ |
| SoyAgeing | 198             | 4,950    | 4,950  |
| SoyGene   | 1,110           | 12,763   | 11,143 |
| Cotton80  | 80              | 240      | 240    |
| SoyLocal  | 200             | 600      | 600    |
| SoyGlobal | 1,938           | 5,814    | 5,814  |

## Supported Tasks
- `image-classification`: Standard supervised classification on labeled subsets.

## Dataset Structure
Each subset (e.g., SoyAgeing-R1, SoyAgeing-R3, etc.) contains:

```
ultra-fgvc/
├── SoyAgeing/
│   ├── SoyAgeing-R1.zip/
│   │   ├── anno/
│   │   │   └── {test, train, val}.txt
│   │   └── images/
│   │   │   └── yd012_R1_{1-10}_{train,test}.png
│   └── ...
├── SoyGene/
│   ├── SoyGene-Part-1.zip
│   └── ...
└── README.md
```

## Citation
If you use this dataset, please cite the following papers:

```bibtex
@inproceedings{yu2021benchmark,
  title     = {Benchmark Platform for Ultra-Fine-Grained Visual Categorization Beyond Human Performance},
  author    = {Yu, Xiaohan and Zhao, Yang and Gao, Yongsheng and Yuan, Xiaohui and Xiong, Shengwu},
  booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
  pages     = {10285--10295},
  year      = {2021}
}
```

## License
This dataset is distributed under the MIT License.

## Source
- Original dataset: https://github.com/XiaohanYu-GU/Ultra-FGVC