- Description:
The Quick Draw Dataset is a collection of 50 million drawings across 345 categories, contributed by players of the game Quick, Draw!. The bitmap dataset contains these drawings converted from vector format into 28x28 grayscale images
Additional Documentation: Explore on Papers With Code
Homepage: https://github.com/googlecreativelab/quickdraw-dataset
Source code:
tfds.datasets.quickdraw_bitmap.Builder
Versions:
3.0.0
(default): New split API (https://tensorflow.org/datasets/splits)
Download size:
36.82 GiB
Dataset size:
Unknown size
Auto-cached (documentation): Unknown
Splits:
Split | Examples |
---|---|
'train' |
50,426,266 |
- Feature structure:
FeaturesDict({
'image': Image(shape=(28, 28, 1), dtype=uint8),
'label': ClassLabel(shape=(), dtype=int64, num_classes=345),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
image | Image | (28, 28, 1) | uint8 | |
label | ClassLabel | int64 |
Supervised keys (See
as_supervised
doc):('image', 'label')
Figure (tfds.show_examples):
- Examples (tfds.as_dataframe):
- Citation:
@article{DBLP:journals/corr/HaE17,
author = {David Ha and
Douglas Eck},
title = {A Neural Representation of Sketch Drawings},
journal = {CoRR},
volume = {abs/1704.03477},
year = {2017},
url = {http://arxiv.org/abs/1704.03477},
archivePrefix = {arXiv},
eprint = {1704.03477},
timestamp = {Mon, 13 Aug 2018 16:48:30 +0200},
biburl = {https://dblp.org/rec/bib/journals/corr/HaE17},
bibsource = {dblp computer science bibliography, https://dblp.org}
}