metadata

license: apache-2.0
dataset_info:
  features:
    - name: screenId
      dtype: int64
    - name: bbox
      sequence: float64
    - name: captions
      sequence: string
    - name: file_name
      dtype: string
    - name: view_hierarchy
      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: 17838159558.65
      num_examples: 71350
  download_size: 2142847271
  dataset_size: 17838159558.65
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
task_categories:
  - image-to-text
language:
  - en
tags:
  - synthetic
  - screens
pretty_name: RICO SCA
size_categories:
  - 10K<n<100K

Dataset Card for RICO SCA (SeeClick cache)

This is the SeeClick cache of a syntehtically generated dataset following RICO SCA's generation procedure. It consists of approximately 170k captions across 70k widgets and 18k screens.

Dataset Details

Dataset Description

This is a widget captioning (referring expression comprehension/generation) dataset.

Curated by: Google Research, Nanjing University
Language(s) (NLP): en
License: apache-2.0

Dataset Sources

Repository: RICO SCA Repo / SeeClick Repo
Paper [optional]: RICO SCA paper / SeeClick paper

Uses

Direct Use

Training models that can be used to understand screens, explain mobile interaces, and act in an automated, digital context.

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.
SCA rationale: Primarily to benefit efforts to create more assitive technologies for visually-impaired users

Source Data

RICO: Mobile app screenshots, collected on Android devices.
SCA: Generated from a trained model

Citation

RICO

BibTeX:

@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).

RICO SCA

BibTeX:

@inproceedings{li2020mapping,
  title={Mapping Natural Language Instructions to Mobile UI Action Sequences},
  author={Li, Yang and He, Jiacong and Zhou, Xin and Zhang, Yuan and Baldridge, Jason},
  booktitle={Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},
  pages={8198--8210},
  year={2020}
}

APA:

Li, Y., He, J., Zhou, X., Zhang, Y., & Baldridge, J. (2020, July). Mapping Natural Language Instructions to Mobile UI Action Sequences. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (pp. 8198-8210).

SeeClick

BibTeX:

@misc{cheng2024seeclick,
      title={SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents}, 
      author={Kanzhi Cheng and Qiushi Sun and Yougang Chu and Fangzhi Xu and Yantao Li and Jianbing Zhang and Zhiyong Wu},
      year={2024},
      eprint={2401.10935},
      archivePrefix={arXiv},
      primaryClass={cs.HC}
}

APA:

Cheng, K., Sun, Q., Chu, Y., Xu, F., Li, Y., Zhang, J., & Wu, Z. (2024). Seeclick: Harnessing gui grounding for advanced visual gui agents. arXiv preprint arXiv:2401.10935.

Dataset Card Authors

Hunter Heidenreich, Roots Automation

Dataset Card Contact

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