# svhn_cropped

<br />

- **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](https://paperswithcode.com/dataset/svhn)

- **Homepage** :
  <http://ufldl.stanford.edu/housenumbers/>

- **Source code** :
  [`tfds.datasets.svhn_cropped.Builder`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/datasets/svhn_cropped/svhn_cropped_dataset_builder.py)

- **Versions**:

  - **`3.1.0`** (default): New split API (<https://tensorflow.org/datasets/splits>)
- **Download size** : `1.47 GiB`

- **Dataset size** : `1.09 GiB`

- **Auto-cached**
  ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):
  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_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):
  `('image', 'label')`

- **Figure**
  ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):

![Visualization](https://storage.googleapis.com/tfds-data/visualization/fig/svhn_cropped-3.1.0.png)

- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):

<button id="displaydataframe">Display examples...</button>

- **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}
    }