Arc
defaults write company.thebrowser.Browser.plist ExtensionManifestV2Availability -int 2
Chrome
defaults write com.google.Chrome.plist ExtensionManifestV2Availability -int 2
Chrome Beta
Arc
defaults write company.thebrowser.Browser.plist ExtensionManifestV2Availability -int 2
Chrome
defaults write com.google.Chrome.plist ExtensionManifestV2Availability -int 2
Chrome Beta
| javascript: (() => { var prefix="https://archive.is/newest/"; var wlh = window.location.href; if (!wlh.startsWith(prefix) && (!wlh.startsWith("https://archive.ph/"))) { window.location.href = prefix + wlh.split("?",1)[0]; } })(); |
Create a openVPN server on Google Cloud Platform to connect to your Google Cloud network using openVPN and/or to route your internet traffic through the VPN (Road Warrior Scenario)
| $ pxctest list-tests \ | |
| --testrun KIF_iphonesimulator10.2-i386.xctestrun \ | |
| | jq -r '. | select(.event | test("begin-test$")) | "\(.className)/\(.methodName)"' | |
| AccessibilityIdentifierTests/testClearingAndEnteringTextIntoViewWithAccessibilityLabel | |
| AccessibilityIdentifierTests/testEnteringTextIntoViewWithAccessibilityIdentifier | |
| AccessibilityIdentifierTests/testEnteringTextIntoViewWithAccessibilityIdentifierExpectingResults | |
| AccessibilityIdentifierTests/testLongPressingViewWithAccessibilityIdentifier | |
| AccessibilityIdentifierTests/testSettingTextIntoViewWithAccessibilityIdentifier | |
| AccessibilityIdentifierTests/testTappingStepperDecrement |
| man() { | |
| env \ | |
| LESS_TERMCAP_mb=$(printf "\e[1;31m") \ | |
| LESS_TERMCAP_md=$(printf "\e[1;31m") \ | |
| LESS_TERMCAP_me=$(printf "\e[0m") \ | |
| LESS_TERMCAP_se=$(printf "\e[0m") \ | |
| LESS_TERMCAP_so=$(printf "\e[1;44;33m") \ | |
| LESS_TERMCAP_ue=$(printf "\e[0m") \ | |
| LESS_TERMCAP_us=$(printf "\e[1;32m") \ | |
| man "$@" |
An experimental change for fast Clojure REPL startup:
java -jar clojure-1.8.0-fast.jarThe code used to create this JAR is on GitHub.
What's it doing?
It is:
| alias accio=wget | |
| alias avadaKedavra='rm -f' | |
| alias imperio=sudo | |
| alias priorIncantato='echo `history |tail -n2 |head -n1` | sed "s/[0-9]* //"' | |
| alias stupefy='sleep 5' | |
| alias wingardiumLeviosa=mv | |
| alias sonorus='set -v' | |
| alias quietus='set +v' |
Just a quickie test in Python 3 (using Requests) to see if Google Cloud Vision can be used to effectively OCR a scanned data table and preserve its structure, in the way that products such as ABBYY FineReader can OCR an image and provide Excel-ready output.
The short answer: No. While Cloud Vision provides bounding polygon coordinates in its output, it doesn't provide it at the word or region level, which would be needed to then calculate the data delimiters.
On the other hand, the OCR quality is pretty good, if you just need to identify text anywhere in an image, without regards to its physical coordinates. I've included two examples:
####### 1. A low-resolution photo of road signs
| ### | |
| ### | |
| ### UPDATE: For Win 11, I recommend using this tool in place of this script: | |
| ### https://christitus.com/windows-tool/ | |
| ### https://github.com/ChrisTitusTech/winutil | |
| ### https://www.youtube.com/watch?v=6UQZ5oQg8XA | |
| ### iwr -useb https://christitus.com/win | iex | |
| ### | |
| ### OR take a look at | |
| ### https://github.com/HotCakeX/Harden-Windows-Security |