imagenet_sketch

• Description:

ImageNet-Sketch consists of 50,889 black and white sketch images, 50 for each of the 1000 ImageNet classes. These images were originally collected from Google Image Search for "sketch of __". 100 images were collected and then manually filtered. For classes with fewer than 50 good images, additional images were constructed by flip or rotation.

• Additional Documentation: Explore on Papers With Code

• Homepage: https://github.com/HaohanWang/ImageNet-Sketch

• Source code: tfds.datasets.imagenet_sketch.Builder

• Versions:

  • 1.0.0 (default): Initial release.

• Download size: 7.07 GiB

• Dataset size: 7.61 GiB

• Auto-cached (documentation): No

• Splits:

Split	Examples
'test'	50,889

• Feature structure:

FeaturesDict({
    'file_name': Text(shape=(), dtype=string),
    'image': Image(shape=(None, None, 3), dtype=uint8),
    'label': ClassLabel(shape=(), dtype=int64, num_classes=1000),
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
file_name	Text		string
image	Image	(None, None, 3)	uint8
label	ClassLabel		int64

• Supervised keys (See as_supervised doc): ('image', 'label')

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

• Citation:

@inproceedings{wang2019learning,
        title={Learning Robust Global Representations by Penalizing Local Predictive Power},
        author={Wang, Haohan and Ge, Songwei and Lipton, Zachary and Xing, Eric P},
        booktitle={Advances in Neural Information Processing Systems},
        pages={10506--10518},
        year={2019}
}