We release the UICaption dataset consisting of UI images paired with descriptions of their functionality. This dataset was used to train Lexi, a pre-trained vision and language model for UI language understanding. The dataset and model are presented in "Lexi: Self-Supervised Learning of the UI Language" by Pratyay Banerjee, Shweti Mahajan, Kushal Arora, Chitta Baral, and Oriana Riva.
UICaption is released as a workflow by which you can generate the actual data.
If you used this dataset please cite the following paper:
@inproceedings{oriva:lexi22,
title = {Lexi: Self-Supervised Learning of the UI Language},
author = {Pratyay Banerjee and Shweti Mahajan and Kushal Arora and Chitta Baral and Oriana Riva},
publisher = {Association for Computational Linguistics},
booktitle = {Proc. of the 2022 Conference on Empirical Methods in Natural Language Processing},
year = {2022},
month = {December}
}Use the compiled list of support and how-to websites provided in tech_urls.txt to extract UI images and associated descriptions from the web. Save the output to a folder, e.g., crawled_uidata:
python crawl_uidata.py -i tech_urls.txt -o crawled_uidata
This script will generate three files stored in the specified output folder: ui_images.p which contains URLs of the UI images, ui_alt_texts.csv which contains alt-text associated with each UI image, ui_instructions_preceding.csv and ui_instructions_succeeding.csv which contains texts appearing before and after the image occurence in the webpage respectively.
Then download the UI images:
python download_images.py -i crawled_uidata/ui_images.txt
Finally, use the crawled UI data to assemble the UICaption dataset:
python gen_uicaption_dataset.py -i crawled_uidata -o ui_caption_dataset.json
The same UI image may appear in multiple websites, hence the script associates one or multiple alt-text descriptions and instructions with each UI image. The script produces a json file with the following format:
| Name | Description |
|---|---|
| image_path | path at which the UI image is stored |
| alt_text_list | one or multiple alt-texts associated with the UI image |
| instruction_list | one or more instructions associated with the UI image |
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