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---
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pretty_name: Cartoon Set
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size_categories:
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- 10K<n<100K
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task_categories:
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- image-classification
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license: cc-by-4.0
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---
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# Dataset Card for Cartoon Set
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## Table of Contents
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- [Dataset Card for Cartoon Set](#dataset-card-for-cartoon-set)
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- [Table of Contents](#table-of-contents)
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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- [Languages](#languages)
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- [Dataset Structure](#dataset-structure)
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- [Data Instances](#data-instances)
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- [Data Fields](#data-fields)
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- [Data Splits](#data-splits)
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- [Dataset Creation](#dataset-creation)
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- [Curation Rationale](#curation-rationale)
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- [Source Data](#source-data)
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- [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
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- [Who are the source language producers?](#who-are-the-source-language-producers)
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- [Annotations](#annotations)
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- [Annotation process](#annotation-process)
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- [Who are the annotators?](#who-are-the-annotators)
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- [Personal and Sensitive Information](#personal-and-sensitive-information)
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- [Considerations for Using the Data](#considerations-for-using-the-data)
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- [Social Impact of Dataset](#social-impact-of-dataset)
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- [Discussion of Biases](#discussion-of-biases)
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- [Other Known Limitations](#other-known-limitations)
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- [Additional Information](#additional-information)
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- [Dataset Curators](#dataset-curators)
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- [Licensing Information](#licensing-information)
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- [Citation Information](#citation-information)
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- [Contributions](#contributions)
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## Dataset Description
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- **Homepage:** https://google.github.io/cartoonset/
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- **Repository:**
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- **Paper:** XGAN: Unsupervised Image-to-Image Translation for Many-to-Many Mappings
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- **Leaderboard:**
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- **Point of Contact:**
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### Dataset Summary
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Cartoon Set is a collection of random, 2D cartoon avatar images. The cartoons vary in 10 artwork categories, 4 color categories, and 4 proportion categories, with a total of ~1013 possible combinations. We provide sets of 10k and 100k randomly chosen cartoons and labeled attributes.
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### Supported Tasks and Leaderboards
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- `image-classification`: The goal of this task is to classify a given image into one of 10 classes. The leaderboard is available [here](https://paperswithcode.com/sota/image-classification-on-Cartoon Set).
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### Languages
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English
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## Dataset Structure
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### Data Instances
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A sample from the training set is provided below:
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```
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{
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'img': <PIL.PngImagePlugin.PngImageFile image mode=RGB size=32x32 at 0x201FA6EE748>,
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'label': 0
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}
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```
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### Data Fields
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- img: A `PIL.Image.Image` object containing the 32x32 image. Note that when accessing the image column: `dataset[0]["image"]` the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the `"image"` column, *i.e.* `dataset[0]["image"]` should **always** be preferred over `dataset["image"][0]`
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- label: 0-9 with the following correspondence
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0 airplane
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1 automobile
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2 bird
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3 cat
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4 deer
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5 dog
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6 frog
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7 horse
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8 ship
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9 truck
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### Data Splits
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Train and Test
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## Dataset Creation
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### Curation Rationale
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[More Information Needed]
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### Source Data
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#### Initial Data Collection and Normalization
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[More Information Needed]
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#### Who are the source language producers?
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[More Information Needed]
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### Annotations
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#### Annotation process
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[More Information Needed]
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#### Who are the annotators?
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[More Information Needed]
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### Personal and Sensitive Information
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[More Information Needed]
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## Considerations for Using the Data
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### Social Impact of Dataset
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[More Information Needed]
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### Discussion of Biases
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[More Information Needed]
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### Other Known Limitations
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[More Information Needed]
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## Additional Information
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### Dataset Curators
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[More Information Needed]
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### Licensing Information
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[More Information Needed]
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### Citation Information
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```
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@TECHREPORT{Krizhevsky09learningmultiple,
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author = {Alex Krizhevsky},
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title = {Learning multiple layers of features from tiny images},
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institution = {},
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year = {2009}
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}
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```
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### Contributions
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Thanks to [@czabo](https://github.com/czabo) for adding this dataset. |
