# scene_parse150

<br />

- **Description**:

Scene parsing is to segment and parse an image into different image regions
associated with semantic categories, such as sky, road, person, and bed. MIT
Scene Parsing Benchmark (SceneParse150) provides a standard training and
evaluation platform for the algorithms of scene parsing.

- **Additional Documentation** :
  [Explore on Papers With Code](https://paperswithcode.com/dataset/ade20k)

- **Homepage** :
  <http://sceneparsing.csail.mit.edu/>

- **Source code** :
  [`tfds.datasets.scene_parse150.Builder`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/datasets/scene_parse150/scene_parse150_dataset_builder.py)

- **Versions**:

  - **`1.0.0`** (default): No release notes.
- **Download size** : `936.97 MiB`

- **Dataset size** : `904.91 MiB`

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

- **Splits**:

| Split | Examples |
|---|---|
| `'test'` | 2,000 |
| `'train'` | 20,210 |

- **Feature structure**:

    FeaturesDict({
        'annotation': Image(shape=(None, None, 3), dtype=uint8),
        'image': Image(shape=(None, None, 3), dtype=uint8),
    })

- **Feature documentation**:

| Feature | Class | Shape | Dtype | Description |
|---|---|---|---|---|
|   | FeaturesDict |   |   |   |
| annotation | Image | (None, None, 3) | uint8 |   |
| image | Image | (None, None, 3) | uint8 |   |

- **Supervised keys** (See
  [`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):
  `('image', 'annotation')`

- **Figure**
  ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):
  Not supported.

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

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

- **Citation**:

    @inproceedings{zhou2017scene,
    title={Scene Parsing through ADE20K Dataset},
    author={Zhou, Bolei and Zhao, Hang and Puig, Xavier and Fidler, Sanja and Barriuso, Adela and Torralba, Antonio},
    booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
    year={2017}
    }