- 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
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}
}