UIED: A Hybrid Tool for GUI Element Detection (Video, ESEC/FSE 2020) скачать в хорошем качестве

UIED: A Hybrid Tool for GUI Element Detection (Video, ESEC/FSE 2020)

"UIED: A Hybrid Tool for GUI Element Detection (Video, ESEC/FSE 2020) Mulong Xie, Sidong Feng, Zhenchang Xing, Jieshan Chen, and Chunyang Chen (Australian National University, Australia; Australian National University, Australia; Australian National University, Australia; Australian National University, Australia; Monash University, Australia) Abstract: Graphical User Interface (GUI) elements detection is critical for many GUI automation and GUI testing tasks. Acquiring the accurate positions and classes of GUI elements is also the very first step to conduct GUI reverse engineering or perform GUI testing. In this paper, we implement a User Iterface Element Detection (UIED), a toolkit designed to provide user with a simple and easy-to-use platform to achieve accurate GUI element detection. UIED integrates multiple detection methods including old-fashioned computer vision (CV) approaches and deep learning models to handle diverse and complicated GUI images. Besides, it equips with a novel customized GUI element detection methods to produce state-of-the-art detection results. Our tool enables the user to change and edit the detection result in an interactive dashboard. Finally, it exports the detected UI elements in the GUI image to design files that can be further edited in popular UI design tools such as Sketch and Photoshop. UIED is evaluated to be capable of accurate detection and useful for downstream works. Tool URL: http://uied.online Github Link: https://github.com/MulongXie/UIED Article: https://doi.org/10.1145/3368089.3417940 Supplementary web page: http://www.uied.online/ Submitted to the conference by Mulong Xie on 2020-10-29 Video Tags: Object Detection, User Interface, Deep Learning, Computer Vision, fse20demo-p40-p, DOI: 10.1145/3368089.3417940 Presentation at the ESEC/FSE 2020 conference, November 8–13, 2020, https://2020.esec-fse.org/ Sponsored by ACM SIGSOFT, https://www.sigsoft.org/ Twitter:   / fseconf   Reddit:   / esecfse  "