您需要先安装一个扩展,例如 篡改猴、Greasemonkey 或 暴力猴,之后才能安装此脚本。
您需要先安装一个扩展,例如 篡改猴 或 暴力猴,之后才能安装此脚本。
您需要先安装一个扩展,例如 篡改猴 或 暴力猴,之后才能安装此脚本。
您需要先安装一个扩展,例如 篡改猴 或 Userscripts ,之后才能安装此脚本。
您需要先安装一款用户脚本管理器扩展,例如 Tampermonkey,才能安装此脚本。
您需要先安装用户脚本管理器扩展后才能安装此脚本。
Unblur Tinder fast match teasers
Tinder Unblur is an advanced userscript that allows you to automatically unlock and view the blurred images of "fast match" teasers on Tinder. The script seamlessly replaces blurred images with the original ones upon page load, enabling you to see who has liked you without any additional actions. Additionally, it provides an interactive button for manual unblurring when desired.
MutationObserver
to detect and automatically unblur new images loaded dynamically without requiring further user intervention.Install Tampermonkey:
Add the Script:
Go to Tinder:
Automatic Unblur:
Manual Unblur (Optional):
Enjoy the Results:
Privacy:
Compatibility:
Improvements and Fixes:
Syntax Corrections:
`
) for template strings to ensure proper construction of image URLs.backgroundImage
property values to prevent syntax errors.Error Handling:
try-catch
blocks to capture and log any errors during the execution of the unblur
function.DOM Selection Optimization:
.Expand.enterAnimationContainer > div:nth-child(1)
to ensure accurate targeting of teaser elements within Tinder's DOM.Dynamic Content Loading Support:
MutationObserver
: Added an observer to detect the addition of new nodes to the DOM and automatically apply the unblur
function to dynamically loaded teaser elements.UI/UX Enhancements:
hover
and active
states.Security Enhancements:
Additional Optimizations:
unblur
Function: Implemented a debounce mechanism to prevent excessive calls to the unblur
function during rapid teaser loading.Other Improvements:
unblur
function to ensure all DOM elements are fully loaded.Initial Release:
Core Functionality:
User Interface:
Automated Execution:
unblur
function upon the full loading of the page.Contributions and improvements are welcome! Feel free to open a pull request or report issues on the GitHub repository.
This project is licensed under the MIT License.
Manolo Zocco
GitHub
2024
QingJ © 2025
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