Background
Common pain points of Android automation tools include misrecognition of elements, poor interface adaptation, etc. DroidRun solves this industry problem through multimodal parsing technology.
Core Solutions
- Double parsing mechanism:Enable "Visual + UI Extraction" mode in Settings to analyze screenshots and system UI data simultaneously
- Sensitivity adjustment:Go to Settings>Recognition Sensitivity, it is recommended to keep the default value of 50 for the first time, and increase or decrease 5-10 units when encountering misrecognition.
- Element highlighting is confirmed:Observe the blue highlighted area while the mission is running to ensure that the elements recognized by the AI are consistent with the target
- Log analysis:View the operation log after each execution to record the location of common misrecognized elements
advanced skill
For special interfaces (e.g. game HUDs): 1) Take screenshots in advance to mark key areas 2) Use the "Save Template" function to solidify the path to success 3) Add textual descriptive features to dynamic elements.
This answer comes from the articleDroidRun: an open source tool for AI to automate Android phonesThe
May not be reproduced without permission:AI productivity tools " How to solve the problem of imprecise automation on Android phones?
English 
简体中文 
日本語 
Deutsch 
Português do Brasil