RICO-Screen2Words / README.md
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---
language:
- en
license: cc-by-4.0
size_categories:
- 10K<n<100K
task_categories:
- image-to-text
pretty_name: Screen2Words
tags:
- screens
- mobile
- phones
dataset_info:
features:
- name: screenId
dtype: int64
- name: captions
sequence: string
- name: file_name
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: file_name_semantic
dtype: string
- name: semantic_annotations
dtype: string
- name: view_hierarchy
dtype: string
- name: image
dtype: image
- name: image_icon
dtype: image
- name: image_semantic
dtype: image
splits:
- name: train
num_bytes: 3618314253.896
num_examples: 15743
- name: val
num_bytes: 520496985.148
num_examples: 2364
- name: test
num_bytes: 956009390.03
num_examples: 4310
download_size: 2473562659
dataset_size: 5094820629.073999
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: val
path: data/val-*
- split: test
path: data/test-*
---
# Dataset Card for Screen2Words
Screen2Words is a dataset providing screen summaries (i.e., image captions for mobile screens).
It uses the RICO image database.
## Dataset Details
### Dataset Description
- **Curated by:** Google Research, UIUC, Northwestern, University of Toronto
- **Funded by:** Google Research
- **Shared by:** Google Research
- **Language(s) (NLP):** English
- **License:** CC-BY-4.0
### Dataset Sources
- **Repository:**
- [google-research-datasets/screen2words](https://github.com/google-research-datasets/screen2words)
- [RICO raw downloads](http://www.interactionmining.org/rico.html)
- **Paper:**
- [Screen2Words: Automatic Mobile UI Summarization with Multimodal Learning](https://arxiv.org/abs/2108.03353)
- [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
- Automatic screen summarization & description
- Language-Based UI retreival (given a UI, retreive similar interfaces)
- Enhancing screen readers
- Screen indexing
- Conversational mobile applications
## 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
- `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.
- `view_hierarchy`: Full view-hierarchy
## 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.
- Screen2Words rationale: Create a dataset that facilities the distillation of screenshots into concise summaries
### Source Data
- RICO: Mobile app screenshots, collected on Android devices.
- Screen2Words: Human annotated screen summaries from paid contractors.
#### Data Collection and Processing
- RICO: Human and automated collection of Android screens. ~9.8k free apps from the Google Play Store.
- Screen2Words: Takes the subset of screens used in RICO-SCA, which 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.
- Screen2Words: 85 professional annotators
## 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).
### Screen2Words
**BibTeX:**
```misc
@inproceedings{wang2021screen2words,
title={Screen2words: Automatic mobile UI summarization with multimodal learning},
author={Wang, Bryan and Li, Gang and Zhou, Xin and Chen, Zhourong and Grossman, Tovi and Li, Yang},
booktitle={The 34th Annual ACM Symposium on User Interface Software and Technology},
pages={498--510},
year={2021}
}
```
**APA:**
Wang, B., Li, G., Zhou, X., Chen, Z., Grossman, T., & Li, Y. (2021, October). Screen2words: Automatic mobile UI summarization with multimodal learning. In The 34th Annual ACM Symposium on User Interface Software and Technology (pp. 498-510).
## Dataset Card Authors
Hunter Heidenreich, Roots Automation
## Dataset Card Contact
hunter "DOT" heidenreich "AT" rootsautomation "DOT" com