# visual_domain_decathlon

<br />

- **Description**:

This contains the 10 datasets used in the Visual Domain Decathlon, part of the
PASCAL in Detail Workshop Challenge (CVPR 2017). The goal of this challenge is
to solve simultaneously ten image classification problems representative of very
different visual domains.

Some of the datasets included here are also available as separate datasets in
TFDS. However, notice that images were preprocessed for the Visual Domain
Decathlon (resized isotropically to have a shorter size of 72 pixels) and might
have different train/validation/test splits. Here we use the official splits for
the competition.

- **Additional Documentation** :
  [Explore on Papers With Code](https://paperswithcode.com/dataset/visual-domain-decathlon)

- **Homepage** :
  [https://www.robots.ox.ac.uk/\~vgg/decathlon/](https://www.robots.ox.ac.uk/%7Evgg/decathlon/)

- **Source code** :
  [`tfds.image_classification.VisualDomainDecathlon`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/image_classification/visual_domain_decathlon.py)

- **Versions**:

  - **`1.2.0`** (default): No release notes.
- **Supervised keys** (See
  [`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):
  `('image', 'label')`

- **Citation**:

    @ONLINE{hakanbilensylvestrerebuffitomasjakab2017,
        author = "Hakan Bilen, Sylvestre Rebuffi, Tomas Jakab",
        title  = "Visual Domain Decathlon",
        year   = "2017",
        url    = "https://www.robots.ox.ac.uk/~vgg/decathlon/"
    }

## visual_domain_decathlon/aircraft (default config)

- **Config description**: Data based on "Aircraft", with images resized
  isotropically to have a shorter size of 72 pixels.

- **Download size** : `409.94 MiB`

- **Dataset size** : `20.96 MiB`

- **Auto-cached**
  ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):
  Yes

- **Splits**:

| Split | Examples |
|---|---|
| `'test'` | 3,333 |
| `'train'` | 3,334 |
| `'validation'` | 3,333 |

- **Feature structure**:

    FeaturesDict({
        'image': Image(shape=(None, None, 3), dtype=uint8),
        'label': ClassLabel(shape=(), dtype=int64, num_classes=100),
        'name': Text(shape=(), dtype=string),
    })

- **Feature documentation**:

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

- **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/visual_domain_decathlon-aircraft-1.2.0.png)

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

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

## visual_domain_decathlon/cifar100

- **Config description**: Data based on "CIFAR-100", with images resized
  isotropically to have a shorter size of 72 pixels.

- **Download size** : `409.94 MiB`

- **Dataset size** : `119.43 MiB`

- **Auto-cached**
  ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):
  Yes

- **Splits**:

| Split | Examples |
|---|---|
| `'test'` | 10,000 |
| `'train'` | 40,000 |
| `'validation'` | 10,000 |

- **Feature structure**:

    FeaturesDict({
        'image': Image(shape=(None, None, 3), dtype=uint8),
        'label': ClassLabel(shape=(), dtype=int64, num_classes=100),
        'name': Text(shape=(), dtype=string),
    })

- **Feature documentation**:

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

- **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/visual_domain_decathlon-cifar100-1.2.0.png)

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

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

## visual_domain_decathlon/daimlerpedcls

- **Config description**: Data based on "Daimler Pedestrian Classification",
  with images resized isotropically to have a shorter size of 72 pixels.

- **Download size** : `409.94 MiB`

- **Dataset size** : `68.35 MiB`

- **Auto-cached**
  ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):
  Yes

- **Splits**:

| Split | Examples |
|---|---|
| `'test'` | 19,600 |
| `'train'` | 23,520 |
| `'validation'` | 5,880 |

- **Feature structure**:

    FeaturesDict({
        'image': Image(shape=(None, None, 3), dtype=uint8),
        'label': ClassLabel(shape=(), dtype=int64, num_classes=2),
        'name': Text(shape=(), dtype=string),
    })

- **Feature documentation**:

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

- **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/visual_domain_decathlon-daimlerpedcls-1.2.0.png)

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

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

## visual_domain_decathlon/dtd

- **Config description**: Data based on "Describable Textures", with images
  resized isotropically to have a shorter size of 72 pixels.

- **Download size** : `409.94 MiB`

- **Dataset size** : `13.30 MiB`

- **Auto-cached**
  ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):
  Yes

- **Splits**:

| Split | Examples |
|---|---|
| `'test'` | 1,880 |
| `'train'` | 1,880 |
| `'validation'` | 1,880 |

- **Feature structure**:

    FeaturesDict({
        'image': Image(shape=(None, None, 3), dtype=uint8),
        'label': ClassLabel(shape=(), dtype=int64, num_classes=47),
        'name': Text(shape=(), dtype=string),
    })

- **Feature documentation**:

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

- **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/visual_domain_decathlon-dtd-1.2.0.png)

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

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

## visual_domain_decathlon/gtsrb

- **Config description**: Data based on "German Traffic Signs", with images
  resized isotropically to have a shorter size of 72 pixels.

- **Download size** : `409.94 MiB`

- **Dataset size** : `80.58 MiB`

- **Auto-cached**
  ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):
  Yes

- **Splits**:

| Split | Examples |
|---|---|
| `'test'` | 12,630 |
| `'train'` | 31,367 |
| `'validation'` | 7,842 |

- **Feature structure**:

    FeaturesDict({
        'image': Image(shape=(None, None, 3), dtype=uint8),
        'label': ClassLabel(shape=(), dtype=int64, num_classes=43),
        'name': Text(shape=(), dtype=string),
    })

- **Feature documentation**:

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

- **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/visual_domain_decathlon-gtsrb-1.2.0.png)

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

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

## visual_domain_decathlon/imagenet12

- **Config description**: Data based on "Imagenet", with images resized
  isotropically to have a shorter size of 72 pixels.

- **Download size** : `6.11 GiB`

- **Dataset size** : `5.24 GiB`

- **Auto-cached**
  ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):
  No

- **Splits**:

| Split | Examples |
|---|---|
| `'test'` | 48,238 |
| `'train'` | 1,232,167 |
| `'validation'` | 49,000 |

- **Feature structure**:

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

- **Feature documentation**:

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

- **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/visual_domain_decathlon-imagenet12-1.2.0.png)

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

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

## visual_domain_decathlon/omniglot

- **Config description**: Data based on "Omniglot", with images resized
  isotropically to have a shorter size of 72 pixels.

- **Download size** : `409.94 MiB`

- **Dataset size** : `41.46 MiB`

- **Auto-cached**
  ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):
  Yes

- **Splits**:

| Split | Examples |
|---|---|
| `'test'` | 8,115 |
| `'train'` | 17,853 |
| `'validation'` | 6,492 |

- **Feature structure**:

    FeaturesDict({
        'image': Image(shape=(None, None, 3), dtype=uint8),
        'label': ClassLabel(shape=(), dtype=int64, num_classes=1623),
        'name': Text(shape=(), dtype=string),
    })

- **Feature documentation**:

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

- **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/visual_domain_decathlon-omniglot-1.2.0.png)

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

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

## visual_domain_decathlon/svhn

- **Config description**: Data based on "Street View House Numbers", with
  images resized isotropically to have a shorter size of 72 pixels.

- **Download size** : `409.94 MiB`

- **Dataset size** : `135.32 MiB`

- **Auto-cached**
  ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):
  Yes

- **Splits**:

| Split | Examples |
|---|---|
| `'test'` | 26,032 |
| `'train'` | 47,217 |
| `'validation'` | 26,040 |

- **Feature structure**:

    FeaturesDict({
        'image': Image(shape=(None, None, 3), dtype=uint8),
        'label': ClassLabel(shape=(), dtype=int64, num_classes=10),
        'name': Text(shape=(), dtype=string),
    })

- **Feature documentation**:

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

- **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/visual_domain_decathlon-svhn-1.2.0.png)

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

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

## visual_domain_decathlon/ucf101

- **Config description**: Data based on "UCF101 Dynamic Images", with images
  resized isotropically to have a shorter size of 72 pixels.

- **Download size** : `409.94 MiB`

- **Dataset size** : `19.73 MiB`

- **Auto-cached**
  ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):
  Yes

- **Splits**:

| Split | Examples |
|---|---|
| `'test'` | 3,783 |
| `'train'` | 7,585 |
| `'validation'` | 1,952 |

- **Feature structure**:

    FeaturesDict({
        'image': Image(shape=(None, None, 3), dtype=uint8),
        'label': ClassLabel(shape=(), dtype=int64, num_classes=101),
        'name': Text(shape=(), dtype=string),
    })

- **Feature documentation**:

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

- **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/visual_domain_decathlon-ucf101-1.2.0.png)

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

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

## visual_domain_decathlon/vgg-flowers

- **Config description**: Data based on "VGG-Flowers", with images resized
  isotropically to have a shorter size of 72 pixels.

- **Download size** : `409.94 MiB`

- **Dataset size** : `20.87 MiB`

- **Auto-cached**
  ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):
  Yes

- **Splits**:

| Split | Examples |
|---|---|
| `'test'` | 6,149 |
| `'train'` | 1,020 |
| `'validation'` | 1,020 |

- **Feature structure**:

    FeaturesDict({
        'image': Image(shape=(None, None, 3), dtype=uint8),
        'label': ClassLabel(shape=(), dtype=int64, num_classes=102),
        'name': Text(shape=(), dtype=string),
    })

- **Feature documentation**:

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

- **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/visual_domain_decathlon-vgg-flowers-1.2.0.png)

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

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