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language:
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language_creators:
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license:
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multilinguality:
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          '7': Allerta Stencil
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          '103': Im Fell
          '104': Im Fell Dw Pica Sc
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          '107': Italianno
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          '110': Josefin Slab
          '111': Julius Sans One
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          '114': Just Me Again Down Here
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          '121': Knewave Outline
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          '123': Kristi
          '124': Kumar One
          '125': Kumar One Outline
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          '131': League Script
          '132': Lemon Tuesday
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          '135': Londrina Shadow
          '136': Londrina Sketch
          '137': Loved By The King
          '138': Lovers Quarrel
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          '141': Mate
          '142': Maven Pro
          '143': Meddon
          '144': Medula One
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          '155': Mr De Haviland
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          '182': Permanent Marker
          '183': Petit Formal Script
          '184': Philosopher
          '185': Pinyon Script
          '186': Pirou
          '187': Play
          '188': Playball
          '189': Playfair Display
          '190': Playlist Caps
          '191': Playlist Script
          '192': Podkova
          '193': Poiret One
          '194': Pompiere
          '195': Port Lligat Slab
          '196': Press Start 2P
          '197': Prompt
          '198': Pt Sans
          '199': Quattrocento
          '200': Quicksand
          '201': Racing Sans One
          '202': Radley
          '203': Rakkas
          '204': Raleway
          '205': Raleway Dots
          '206': Rammetto One
          '207': Rationale
          '208': Reem Kufi
          '209': Reenie Beanie
          '210': Righteous
          '211': Rise
          '212': Rissa Typeface
          '213': Roboto
          '214': Rochester
          '215': Rock Salt
          '216': Rokkitt
          '217': Rosario
          '218': Rubik
          '219': Rubik One
          '220': Ruslan Display
          '221': Russo One
          '222': Rye
          '223': Sacramento
          '224': Sansita One
          '225': Satisfy
          '226': Scope One
          '227': Secular One
          '228': Selima Script
          '229': Sensei
          '230': Seymour One
          '231': Shadows Into Light Two
          '232': Share Tech Mono
          '233': Sirin Stencil
          '234': Six Caps
          '235': Source Serif Pro
          '236': Space Mono
          '237': Stalemate
          '238': Stint Ultra Expanded
          '239': Sue Ellen Francisco
          '240': Suez One
          '241': Sunday
          '242': Superclarendon Regular
          '243': Text Me One
          '244': Tinos
          '245': Titillium Web
          '246': Tulpen One
          '247': Underdog
          '248': V T323
          '249': Vampiro One
          '250': Varela Round
          '251': Vast Shadow
          '252': Vollkorn
          '253': Waiting For The Sunrise
          '254': Wire One
          '255': Yanone Kaffeesatz
          '256': Yellowtail
          '257': Yeseva One
          '258': Yesteryear
          '259': Zeyada
          '260': Znikomit
          '261': Znikomitno24
  - name: font_size
    sequence: float32
  - name: text_align
    sequence:
      class_label:
        names:
          '0': ''
          '1': center
          '2': left
          '3': right
  - name: angle
    sequence: float32
  - name: capitalize
    sequence:
      class_label:
        names:
          '0': 'false'
          '1': 'true'
  - name: line_height
    sequence: float32
  - name: letter_spacing
    sequence: float32
  - name: color
    sequence:
      sequence: float32
      length: 3
  - name: image
    sequence: image
  splits:
  - name: train
    num_bytes: 3259312504.503
    num_examples: 18659
  - name: test
    num_bytes: 413774119.686
    num_examples: 2371
  - name: validation
    num_bytes: 418393287.999
    num_examples: 2391
  download_size: 4054319749
  dataset_size: 4091479912.1879997
---

# Dataset Card for Crello

## Table of Contents
- [Dataset Card for Crello](#dataset-card-for-crello)
  - [Table of Contents](#table-of-contents)
  - [Dataset Description](#dataset-description)
    - [Dataset Summary](#dataset-summary)
    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
    - [Languages](#languages)
  - [Dataset Structure](#dataset-structure)
    - [Data Instances](#data-instances)
    - [Data Fields](#data-fields)
    - [Data Splits](#data-splits)
  - [Dataset Creation](#dataset-creation)
    - [Curation Rationale](#curation-rationale)
    - [Source Data](#source-data)
      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
      - [Who are the source language producers?](#who-are-the-source-language-producers)
    - [Personal and Sensitive Information](#personal-and-sensitive-information)
  - [Considerations for Using the Data](#considerations-for-using-the-data)
    - [Social Impact of Dataset](#social-impact-of-dataset)
    - [Discussion of Biases](#discussion-of-biases)
    - [Other Known Limitations](#other-known-limitations)
  - [Additional Information](#additional-information)
    - [Dataset Curators](#dataset-curators)
    - [Licensing Information](#licensing-information)
    - [Citation Information](#citation-information)
    - [Contributions](#contributions)

## Dataset Description

- **Homepage:** [CanvasVAE github](https://github.com/CyberAgentAILab/canvas-vae)
- **Repository:**
- **Paper:** [CanvasVAE: Learning to Generate Vector Graphic Documents](https://arxiv.org/abs/2108.01249)
- **Leaderboard:**
- **Point of Contact:** [Kota Yamaguchi](https://github.com/kyamagu)

### Dataset Summary

The Crello dataset is compiled for the study of vector graphic documents. The dataset contains document meta-data such as canvas size and pre-rendered elements such as images or text boxes. The original templates was collected from [crello.com](https://crello.com) (now [create.vista.com](https://create.vista.com/)) and converted to low-resolution format suitable for machine learning analysis.

### Supported Tasks and Leaderboards

[CanvasVAE](https://arxiv.org/abs/2108.01249) studies unsupervised document generation.

### Languages

Almost all design templates use English.

## Dataset Structure

### Data Instances

Each instance has scalar attributes (canvas) and sequence attributes (elements). Categorical values are stored as integer values. Check `ClassLabel` features of the dataset for the list of categorical labels.

```
{'id': '59528b4e95a7a863ddcdf902',
 'length': 14,
 'group': 5,
 'format': 49,
 'canvas_width': 11,
 'canvas_height': 34,
 'category': 14,
 'type': [1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4],
 'left': [0.0002478847454767674,
  0.0,
  0.0,
  0.03125,
  0.05624999850988388,
  0.30000001192092896,
  0.16875000298023224,
  0.18125000596046448,
  0.5625,
  0.3375000059604645,
  0.25623849034309387,
  0.41874998807907104,
  0.19995903968811035,
  0.36250001192092896],
 'top': [0.00042101924191229045,
  0.0,
  -0.0016666667070239782,
  0.008333333767950535,
  0.014999999664723873,
  0.5633333325386047,
  0.4816666543483734,
  0.4116666615009308,
  0.3883333206176758,
  0.3883333206176758,
  0.512499988079071,
  0.4833333194255829,
  0.4350000023841858,
  0.3933333456516266],
 'width': [0.9999237656593323,
  0.9937499761581421,
  1.0,
  0.9375,
  0.8812500238418579,
  0.4000000059604645,
  0.65625,
  0.637499988079071,
  0.09375,
  0.10000000149011612,
  0.6084214448928833,
  0.29374998807907104,
  0.7160975337028503,
  0.28125],
 'height': [1.0023325681686401,
  0.9983333349227905,
  1.0,
  0.9833333492279053,
  0.9683333039283752,
  0.0416666679084301,
  0.04333333298563957,
  0.029999999329447746,
  0.029999999329447746,
  0.029999999329447746,
  0.05166666582226753,
  0.021666666492819786,
  0.05166666582226753,
  0.018333332613110542],
 'opacity': [1.0,
  1.0,
  1.0,
  1.0,
  1.0,
  1.0,
  1.0,
  1.0,
  1.0,
  1.0,
  1.0,
  1.0,
  1.0,
  1.0],
 'text': ['',
  '',
  '',
  '',
  '',
  '',
  '',
  '',
  '',
  '',
  'Nature',
  'with',
  'friends',
  'Make'],
 'font': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 31, 182, 31, 31],
 'font_size': [0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  31.71994972229004,
  13.0,
  31.644691467285156,
  11.0],
 'text_align': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 2, 1],
 'angle': [0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  0.0],
 'capitalize': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
 'line_height': [1.0,
  1.0,
  1.0,
  1.0,
  1.0,
  1.0,
  1.0,
  1.0,
  1.0,
  1.0,
  1.0,
  1.0,
  1.0,
  1.0],
 'letter_spacing': [0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  0.0,
  2.0,
  0.0,
  2.0,
  1.0],
 'color': [[35.0, 80.0, 60.0],
  [255.0, 255.0, 255.0],
  [35.0, 31.0, 32.0],
  [255.0, 255.0, 255.0],
  [255.0, 255.0, 255.0],
  [255.0, 255.0, 255.0],
  [255.0, 255.0, 255.0],
  [255.0, 255.0, 255.0],
  [255.0, 255.0, 255.0],
  [255.0, 255.0, 255.0],
  [255.0, 255.0, 255.0],
  [255.0, 255.0, 255.0],
  [255.0, 255.0, 255.0],
  [255.0, 255.0, 255.0]],
 'image': [<PIL.PngImagePlugin.PngImageFile image mode=RGBA size=256x256>,
  <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=256x256>,
  <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=256x256>,
  <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=256x256>,
  <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=256x256>,
  <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=256x256>,
  <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=256x256>,
  <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=256x256>,
  <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=256x256>,
  <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=256x256>,
  <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=256x256>,
  <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=256x256>,
  <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=256x256>,
  <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=256x256>]}
```

To get a label for categorical values, use the `int2str` method:

```python
key = "font"
example = dataset[0]

dataset.features[key].int2str(example[key])
```

### Data Fields

In the following, categorical fields are shown as `categorical` type, but the actual storage is `int64`.

**Context features (Canvas attributes)**

| Field         | Type        | Shape | Description                                                    |
| ------------- | ----------- | ----- | -------------------------------------------------------------- |
| id            | string      | ()    | Template ID from crello.com                                    |
| group         | categorical | ()    | Broad design group, such as social media posts or blog headers |
| format        | categorical | ()    | Detailed design format, such as Instagram post or postcard     |
| category      | categorical | ()    | Topic category of the design, such as holiday celebration      |
| canvas_width  | categorical | ()    | Canvas pixel width                                             |
| canvas_height | categorical | ()    | Canvas pixel height                                            |
| length        | int64       | ()    | Length of sequence features                                    |

**Sequence features (Element attributes)**

| Field          | Type        | Shape | Description                                                          |
| -------------- | ----------- | ----- | -------------------------------------------------------------------- |
| type           | categorical | ()    | Element type, such as vector shape, image, or text                   |
| left           | float32     | ()    | Element left position normalized to [0, 1] range w.r.t. canvas_width |
| top            | float32     | ()    | Element top position normalized to [0, 1] range w.r.t. canvas_height |
| width          | float32     | ()    | Element width normalized to [0, 1] range w.r.t. canvas_width         |
| height         | float32     | ()    | Element height normalized to [0, 1] range w.r.t. canvas_height       |
| color          | int64       | (3,)  | Extracted main RGB color of the element                              |
| opacity        | float32     | ()    | Opacity in [0, 1] range                                              |
| image_bytes    | image       | ()    | Pre-rendered 256x256 preview of the element encoded in PNG format    |
| text           | string      | ()    | Text content in UTF-8 encoding for text element                      |
| font           | categorical | ()    | Font family name for text element                                    |
| font_size      | float32     | ()    | Font size (height) in pixels                                         |
| text_align     | categorical | ()    | Horizontal text alignment, left, center, right for text element      |
| angle          | float32     | ()    | Element rotation angle (radian) w.r.t. the center of the element     |
| capitalize     | categorical | ()    | Binary flag to capitalize letters                                    |
| line_height    | float32     | ()    | Scaling parameter to line height, default is 1.0                     |
| letter_spacing | float32     | ()    | Adjustment parameter for letter spacing, default is 0.0              |

Note that the color and pre-rendered images do not necessarily accurately reproduce the original design templates. The original template is accessible at the following URL if still available.

```
https://create.vista.com/artboard/?template=<template_id>
```

`left` and `top` can be negative because elements can be bigger than the canvas size.

### Data Splits

The Crello dataset has 3 splits: train, validation, and test. The current split is generated such that the same title of the original template shows up in only in one split.

| Split     | Count |
| --------- | ----- |
| train     | 18659 |
| validaton | 2391  |
| test      | 2371  |


### Visualization

Each example can be visualized in the following approach. Note the following does not guarantee a similar appearance to the original template.

```python
import io
from typing import Any, Dict

import numpy as np
import skia


def render(dataset: datasets.Dataset, example: Dict[str, Any], max_size: float=512.) -> bytes:
    """Render parsed sequence example onto an image and return as PNG bytes."""
    canvas_width = int(dataset.features["canvas_width"].int2str(example["canvas_width"]))
    canvas_height = int(dataset.features["canvas_height"].int2str(example["canvas_height"]))

    scale = min(1.0, max_size / canvas_width, max_size / canvas_height)

    surface = skia.Surface(int(scale * canvas_width), int(scale * canvas_height))
    with surface as canvas:
        canvas.scale(scale, scale)
        for index in range(example["length"]):
            pil_image = example["image"][index]
            image = skia.Image.frombytes(
                pil_image.convert('RGBA').tobytes(),
                pil_image.size,
                skia.kRGBA_8888_ColorType)
            left = example["left"][index] * canvas_width
            top = example["top"][index] * canvas_height
            width = example["width"][index] * canvas_width
            height = example["height"][index] * canvas_height
            rect = skia.Rect.MakeXYWH(left, top, width, height)

            angle = example["angle"][index]
            with skia.AutoCanvasRestore(canvas):
                if angle != 0:
                    degree = 180. * angle / np.pi
                    canvas.rotate(degree, left + width / 2., top + height / 2.)
                canvas.drawImageRect(image, rect)

    image = surface.makeImageSnapshot()
    with io.BytesIO() as f:
        image.save(f, skia.kPNG)
        return f.getvalue()
```


## Dataset Creation

### Curation Rationale

The Crello dataset is compiled for the general study of vector graphic documents, with the goal of producing a dataset that offers complete vector graphic information suitable for neural methodologies.

### Source Data

#### Initial Data Collection and Normalization

The dataset is initially scraped from the former `crello.com`, and pre-processed to

#### Who are the source language producers?

While [create.vista.com](https://create.vista.com/)) owns those templates, the templates seems to be originially created by certain group of design studios.

### Personal and Sensitive Information

The dataset does not contain any personal information about the creator, but may contain a picture of people in the design template.

## Considerations for Using the Data

### Social Impact of Dataset

This dataset was developed for advancing the general study of vector graphic documents, especially for generative systems of graphic design. Successful systems might enable automation of creative workflow that human designers get involved in.

### Discussion of Biases

The templates contained in the dataset reflect the biases appearing in the source data, which could present gender biases in specific design categories.

### Other Known Limitations

Due to the unknown data specification of the source data, the color and pre-rendered images do not necessarily accurately reproduce the original design templates. The original template is accessible at the following URL if still available.

    https://create.vista.com/artboard/?template=<template_id>

## Additional Information

### Dataset Curators

The Crello dataset was developed by Kota Yamaguchi.

### Licensing Information

The origin of the dataset is [create.vista.com](https://create.vista.com) (formally, `crello.com`).
The distributor ("We") do not own the copyrights of the original design templates.
By using Crello dataset, the user of this dataset ("You") must agree to the
[VistaCreate License Agreements](https://create.vista.com/faq/legal/licensing/license_agreements/).

The dataset is distributed under [CDLA-Permissive-2.0 license](https://cdla.dev/permissive-2-0/).

**Note**

We do not re-distribute the original files as we are not allowed by terms.

### Citation Information

    @article{yamaguchi2021canvasvae,
      title={CanvasVAE: Learning to Generate Vector Graphic Documents},
      author={Yamaguchi, Kota},
      journal={ICCV},
      year={2021}
    }

### Releases

3.0: v3 release (Feb 8, 2023)

- Migrate to Hugging Face Hub.
- Improve text rendering quality.
- Change split generation criteria: no compatibility with v2 splits.
- Incorporate a motion picture thumbnail in templates.
- Add `capitalize`, `line_height`, and `letter_spacing` sequence attributes.

2.0: v2 release (May 26, 2022)

- Add `text`, `font`, `font_size`, `text_align`, and `angle` sequence attributes.
- Include rendered text element in `image_bytes`.

1.0: v1 release (Aug 24, 2021)


### Contributions

Thanks to [@kyamagu](https://github.com/kyamagu) for adding this dataset.