|
--- |
|
dataset_info: |
|
features: |
|
- name: image |
|
dtype: PIL.Image.Image |
|
- name: label |
|
dtype: int |
|
class_label: |
|
names: |
|
'0': bowtie |
|
'1': windmill |
|
'2': tree |
|
'3': river |
|
'4': ice cream |
|
'5': eye |
|
'6': book |
|
'7': sun |
|
'8': star |
|
'9': airplane |
|
'10': butterfly |
|
'11': clock |
|
'12': car |
|
'13': fish |
|
'14': face |
|
'15': umbrella |
|
'16': cat |
|
'17': bicycle |
|
'18': pizza |
|
'19': house |
|
'20': cake |
|
'21': bucket |
|
'22': crown |
|
'23': light bulb |
|
'24': cell phone |
|
'25': t-shirt |
|
splits: |
|
- name: train |
|
num_bytes: 174683075.2 |
|
num_examples: 416000 |
|
- name: val |
|
num_bytes: 21851140.4 |
|
num_examples: 52000 |
|
- name: test |
|
num_bytes: 21675900.4 |
|
num_examples: 52000 |
|
download_size: 218844448 |
|
dataset_size: 218210116 |
|
configs: |
|
- config_name: default |
|
data_files: |
|
- split: train |
|
path: data/train-* |
|
- split: val |
|
path: data/val-* |
|
- split: test |
|
path: data/test-* |
|
task_categories: |
|
- image-classification |
|
tags: |
|
- art |
|
size_categories: |
|
- 100K<n<1M |
|
--- |
|
|
|
|
|
# Quick! Draw 26 Class Dataset |
|
|
|
This dataset is derived from the Google Quick! Draw dataset and contains 26 classes of doodle images drawn by users. The classes include common objects and entities like animals, vehicles, food items, and everyday objects. |
|
|
|
## Dataset Details |
|
|
|
- **Number of Classes:** 26 |
|
- **Total Images:** 520,000 (416,000 train, 52,000 val, 52,000 test) |
|
- **Image Format:** PNG images of size 28x28 pixels (grayscale) |
|
- **Data Fields:** |
|
- `image`: PIL Image object |
|
- `label`: Integer label corresponding to class |
|
|
|
## Class Labels |
|
|
|
0: bowtie, 1: windmill, 2: tree, 3: river, 4: ice cream, 5: eye, 6: book, 7: sun, 8: star, 9: airplane, 10: butterfly, 11: clock, 12: car, 13: fish, 14: face, 15: umbrella, 16: cat, 17: bicycle, 18: pizza, 19: house, 20: cake, 21: bucket, 22: crown, 23: light bulb, 24: cell phone, 25: t-shirt |
|
|
|
## Download and Loading |
|
|
|
You can load this dataset using the `load_dataset` function from the `datasets` library: |
|
|
|
```python |
|
from datasets import load_dataset |
|
|
|
dataset = load_dataset("OmAlve/quickdraw_26_classes") |
|
``` |
|
|
|
This will download and cache the dataset locally. |
|
|
|
|
|
## Maintainers |
|
|
|
- [Om Alve](https://huggingface.co/OmAlve) |
