# quickdraw_bitmap

<br />

- **Description**:

The Quick Draw Dataset is a collection of 50 million drawings across 345
categories, contributed by players of the game Quick, Draw!. The bitmap dataset
contains these drawings converted from vector format into 28x28 grayscale images

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

- **Homepage** :
  <https://github.com/googlecreativelab/quickdraw-dataset>

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

- **Versions**:

  - **`3.0.0`** (default): New split API (<https://tensorflow.org/datasets/splits>)
- **Download size** : `36.82 GiB`

- **Dataset size** : `Unknown size`

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

- **Splits**:

| Split | Examples |
|---|---|
| `'train'` | 50,426,266 |

- **Feature structure**:

    FeaturesDict({
        'image': Image(shape=(28, 28, 1), dtype=uint8),
        'label': ClassLabel(shape=(), dtype=int64, num_classes=345),
    })

- **Feature documentation**:

| Feature | Class | Shape | Dtype | Description |
|---|---|---|---|---|
|   | FeaturesDict |   |   |   |
| image | Image | (28, 28, 1) | 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/quickdraw_bitmap-3.0.0.png)

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

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

- **Citation**:

    @article{DBLP:journals/corr/HaE17,
      author    = {David Ha and
                   Douglas Eck},
      title     = {A Neural Representation of Sketch Drawings},
      journal   = {CoRR},
      volume    = {abs/1704.03477},
      year      = {2017},
      url       = {http://arxiv.org/abs/1704.03477},
      archivePrefix = {arXiv},
      eprint    = {1704.03477},
      timestamp = {Mon, 13 Aug 2018 16:48:30 +0200},
      biburl    = {https://dblp.org/rec/bib/journals/corr/HaE17},
      bibsource = {dblp computer science bibliography, https://dblp.org}
    }