|
--- |
|
dataset_info: |
|
features: |
|
- name: image |
|
dtype: image |
|
- name: label |
|
dtype: |
|
class_label: |
|
names: |
|
'0': a1 |
|
'1': a2 |
|
'2': a3 |
|
'3': a4 |
|
'4': ammonite |
|
'5': bamboofern |
|
'6': bedder |
|
'7': binary |
|
'8': branch |
|
'9': broccoli |
|
'10': bud |
|
'11': c_curve |
|
'12': castle |
|
'13': cedarleaf |
|
'14': coral |
|
'15': crystal |
|
'16': deerfern |
|
'17': dragon_curve |
|
'18': drumlin |
|
'19': fern |
|
'20': filmyfern |
|
'21': fleabane |
|
'22': flower |
|
'23': gaku |
|
'24': ginkgo |
|
'25': gold_dragon |
|
'26': grassfern |
|
'27': greygoldenrod |
|
'28': groundpine |
|
'29': involucre |
|
'30': koch_curve |
|
'31': koch_snowflake |
|
'32': maple_leaf |
|
'33': mcWorter_pedigree |
|
'34': morningglory |
|
'35': newyorkfern |
|
'36': octopuslegs |
|
'37': penta |
|
'38': pinetree |
|
'39': rose |
|
'40': shieldfern |
|
'41': sierpinski_carpet |
|
'42': sierpinski_gasket |
|
'43': sierpinski_pentagon |
|
'44': snail |
|
'45': snowcap |
|
'46': snowdrift |
|
'47': spiderbrake |
|
'48': spiral |
|
'49': spleenwort_fern |
|
'50': star |
|
'51': sticks |
|
'52': sunflower |
|
'53': supernova |
|
'54': swirl |
|
'55': tree |
|
'56': turbanshell |
|
'57': umbrellafern |
|
'58': watersprite |
|
'59': zigzag |
|
splits: |
|
- name: train |
|
num_bytes: 3588623140 |
|
num_examples: 60000 |
|
download_size: 1829671228 |
|
dataset_size: 3588623140 |
|
configs: |
|
- config_name: default |
|
data_files: |
|
- split: train |
|
path: data/train-* |
|
license: cc-by-4.0 |
|
task_categories: |
|
- image-classification |
|
pretty_name: 'FractalDB 60 ' |
|
size_categories: |
|
- 10K<n<100K |
|
--- |
|
|
|
# FractalDB 60 |
|
|
|
FractalDB 60 dataset from [Pre-training without Natural Images](https://hirokatsukataoka16.github.io/Pretraining-without-Natural-Images/). |
|
|
|
[Original repo](https://github.com/hirokatsukataoka16/FractalDB-Pretrained-ResNet-PyTorch) | [Project page](https://hirokatsukataoka16.github.io/Pretraining-without-Natural-Images/) | [arXiv](https://arxiv.org/abs/2101.08515) |
|
|
|
## Citing |
|
|
|
```bibtex |
|
@article{KataokaIJCV2022, |
|
author={Kataoka, Hirokatsu and Okayasu, Kazushige and Matsumoto, Asato and Yamagata, Eisuke and Yamada, Ryosuke and Inoue, Nakamasa and Nakamura, Akio and Satoh, Yutaka}, |
|
title={Pre-training without Natural Images}, |
|
article={International Journal on Computer Vision (IJCV)}, |
|
year={2022}, |
|
} |
|
|
|
@inproceedings{KataokaACCV2020, |
|
author={Kataoka, Hirokatsu and Okayasu, Kazushige and Matsumoto, Asato and Yamagata, Eisuke and Yamada, Ryosuke and Inoue, Nakamasa and Nakamura, Akio and Satoh, Yutaka}, |
|
title={Pre-training without Natural Images}, |
|
booktitle={Asian Conference on Computer Vision (ACCV)}, |
|
year={2020}, |
|
} |
|
|
|
@misc{kataoka2021pretraining, |
|
title={Pre-training without Natural Images}, |
|
author={Hirokatsu Kataoka and Kazushige Okayasu and Asato Matsumoto and Eisuke Yamagata and Ryosuke Yamada and Nakamasa Inoue and Akio Nakamura and Yutaka Satoh}, |
|
year={2021}, |
|
eprint={2101.08515}, |
|
archivePrefix={arXiv}, |
|
primaryClass={cs.CV} |
|
} |
|
``` |
