README.md

---
language:
- en
license: cc-by-4.0
size_categories:
- 10K<n<100K
task_categories:
- image-to-text
- text-generation
pretty_name: Widget Captioning
tags:
- screens
- mobile
- phones
dataset_info:
  features:
  - name: screenId
    dtype: int64
  - name: captions
    sequence: string
  - name: view_hierarchy
    dtype: string
  - name: bbox
    sequence: float64
  - name: file_name
    dtype: string
  - name: file_name_semantic
    dtype: string
  - name: semantic_annotations
    dtype: string
  - name: app_package_name
    dtype: string
  - name: play_store_name
    dtype: string
  - name: category
    dtype: string
  - name: average_rating
    dtype: float64
  - name: number_of_ratings
    dtype: string
  - name: number_of_downloads
    dtype: string
  - name: file_name_icon
    dtype: string
  - name: image
    dtype: image
  - name: image_icon
    dtype: image
  - name: image_semantic
    dtype: image
  splits:
  - name: train
    num_bytes: 10278117710.220001
    num_examples: 41221
  - name: val
    num_bytes: 880438420.595
    num_examples: 3483
  - name: test
    num_bytes: 987366583.47
    num_examples: 3621
  download_size: 2945501992
  dataset_size: 12145922714.285
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: val
    path: data/val-*
  - split: test
    path: data/test-*
---

# Dataset Card for RICO Widget Captioning

Widget Captioning is a dataset for providing captions for UI elements on mobile screens. 
It uses the RICO image database. 

## Dataset Details

### Dataset Description

- **Curated by:** Google Research, UIUC, Northwestern, Georgia Tech
- **Funded by:** Google Research
- **Shared by:** Google Research
- **Language(s) (NLP):** English
- **License:** CC-BY-4.0

### Dataset Sources 

- **Repository:**
  - [google-research-datasets/widget-caption](https://github.com/google-research-datasets/widget-caption)
  - [RICO raw downloads](http://www.interactionmining.org/rico.html)
- **Paper:**
  - [Widget Captioning: Generating Natural Language Description for Mobile User Interface Elements](https://arxiv.org/abs/2010.04295)
  - [Rico: A Mobile App Dataset for Building Data-Driven Design Applications](https://dl.acm.org/doi/10.1145/3126594.3126651)

## Uses

This dataset is for developing multimodal automations for mobile screens. 

### Direct Use

- Enhancing screen readers
- Screen indexing
- Conversational mobile applications
- Q&A on screens 

## Dataset Structure

- `screenId`: Unique RICO screen ID
- `image`: RICO screenshot
- `image_icon`: Google Play Store icon for the app
- `image_semantic`: Semantic RICO screenshot; details are abstracted away to main visual UI elements
- `file_name`: Image local filename
- `file_name_icon`: Icon image local filename
- `file_name_semantic`: Screenshot Image as a semantic annotated image local filename 
- `captions`: A list of string captions
- `bbox`: The bounding box for the widget being captioned, relatively scaled with the image size so that coordinates are in [0, 1]
- `app_package_name`: Android package name
- `play_store_name`: Google Play Store name
- `category`: Type of category of the app
- `number_of_downloads`: Number of downloads of the app (as a coarse range string)
- `number_of_ratings`: Number of ratings of the app on the Google Play store (as of collection)
- `average_rating`: Average rating of the app on the Google Play Store (as of collection)
- `semantic_annotations`: Reduced view hierarchy, to the semantically-relevant portions of the full view hierarchy. It corresponds to what is visualized in `image_semantic` and has a lot of details about what's on screen. It is stored as a JSON object string.

## Dataset Creation

### Curation Rationale

- RICO rationale: Create a broad dataset that can be used for UI automation. An explicit goal was to develop automation software that can validate an app's design and assess whether it achieves its stated goal.
- Widget Captioning rationale: Create a dataset that helps machines reason about UI elements on screens

### Source Data

- RICO: Mobile app screenshots, collected on Android devices.
- Widget Captioning: Human annotated concise captions for widgets on screen

#### Data Collection and Processing

- RICO: Human and automated collection of Android screens. ~9.8k free apps from the Google Play Store. 
- Widget Captioning: Takes the subset of screens used in RICO, eliminates screens with missing or inaccurate view hierarchies. 

#### Who are the source data producers?

- RICO: 13 human workers (10 from the US, 3 from the Philippines) through UpWork. 
- Widget Captioning: 5.4k annotators through Amazon Mechanical Turk

## Citation

### RICO 

**BibTeX:**

```misc
@inproceedings{deka2017rico,
  title={Rico: A mobile app dataset for building data-driven design applications},
  author={Deka, Biplab and Huang, Zifeng and Franzen, Chad and Hibschman, Joshua and Afergan, Daniel and Li, Yang and Nichols, Jeffrey and Kumar, Ranjitha},
  booktitle={Proceedings of the 30th annual ACM symposium on user interface software and technology},
  pages={845--854},
  year={2017}
}
```

**APA:**

Deka, B., Huang, Z., Franzen, C., Hibschman, J., Afergan, D., Li, Y., ... & Kumar, R. (2017, October). Rico: A mobile app dataset for building data-driven design applications. In Proceedings of the 30th annual ACM symposium on user interface software and technology (pp. 845-854).

### Widget Captioning

**BibTeX:**

```misc
@inproceedings{li2020widget,
  title={Widget Captioning: Generating Natural Language Description for Mobile User Interface Elements},
  author={Li, Yang and Li, Gang and He, Luheng and Zheng, Jingjie and Li, Hong and Guan, Zhiwei},
  booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
  pages={5495--5510},
  year={2020}
}
```

**APA:**

Li, Y., Li, G., He, L., Zheng, J., Li, H., & Guan, Z. (2020, November). Widget Captioning: Generating Natural Language Description for Mobile User Interface Elements. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (pp. 5495-5510).
## Dataset Card Authors

Hunter Heidenreich, Roots Automation

## Dataset Card Contact

hunter "DOT" heidenreich "AT" rootsautomation "DOT" com