- Description:
The Street View House Numbers (SVHN) Dataset is an image digit recognition dataset of over 600,000 digit images coming from real world data. Images are cropped to 32x32.
Additional Documentation: Explore on Papers With Code
Homepage: http://ufldl.stanford.edu/housenumbers/
Source code:
tfds.datasets.svhn_cropped.BuilderVersions:
3.1.0(default): New split API (https://tensorflow.org/datasets/splits)
Download size:
1.47 GiBDataset size:
1.09 GiBAuto-cached (documentation): No
Splits:
| Split | Examples |
|---|---|
'extra' |
531,131 |
'test' |
26,032 |
'train' |
73,257 |
- Feature structure:
FeaturesDict({
'id': Text(shape=(), dtype=string),
'image': Image(shape=(32, 32, 3), dtype=uint8),
'label': ClassLabel(shape=(), dtype=int64, num_classes=10),
})
- Feature documentation:
| Feature | Class | Shape | Dtype | Description |
|---|---|---|---|---|
| FeaturesDict | ||||
| id | Text | string | ||
| image | Image | (32, 32, 3) | uint8 | |
| label | ClassLabel | int64 |
Supervised keys (See
as_superviseddoc):('image', 'label')Figure (tfds.show_examples):
- Examples (tfds.as_dataframe):
- Citation:
"""Street View House Numbers (SVHN) Dataset, cropped version."""
@article{Netzer2011,
author = {Netzer, Yuval and Wang, Tao and Coates, Adam and Bissacco, Alessandro and Wu, Bo and Ng, Andrew Y},
booktitle = {Advances in Neural Information Processing Systems ({NIPS})},
title = {Reading Digits in Natural Images with Unsupervised Feature Learning},
year = {2011}
}