berndverst

{
    "workbench.colorCustomizations": {
        "terminal.foreground": "#839496",
        "terminal.background": "#002833",
        "terminal.ansiBlack": "#003541",
        "terminal.ansiBlue": "#268bd2",
        "terminal.ansiCyan": "#2aa198",
        "terminal.ansiGreen": "#859901",
        "terminal.ansiMagenta": "#d33682",
        "terminal.ansiRed": "#dc322f",

berndverst

alias acr-login="echo 'Fetching available Azure container registries...'; az acr list -otable --query='[*].{Name:name,Group:resourceGroup,Location:location}'; echo '\nEnter registry name:'; read azregistry; az acr credential show -n \$azregistry --query='[passwords[0]][0].value' -otsv | docker login -u \$azregistry --password-stdin \$azregistry.azurecr.io"

berndverst

{
  "swagger": "2.0",
  "info": {
    "version": "2016-09-12T23:19:28Z",
    "title": "ProxyAPIwithCreds"
  },
  "host": "my-domain.com",
  "basePath": "/test",
  "schemes": [
    "https"

berndverst

{
    "$schema": "http://json.schemastore.org/proxies",
    "proxies": {
        "API proxy with Credentials": {
            "matchCondition": {
                "route": "/api/{*route}",
                "methods": [
                    "GET"
                ]
            },

berndverst

AKSNODE=aks-nodepool1-32072832-0; kubectl cordon $AKSNODE && kubectl drain $AKSNODE --ignore-daemonsets=true && echo "$AKSNODE restarting" && az vm restart -g MC_containergroupeast_managedkube_eastus -n $AKSNODE && sleep 10 && kubectl uncordon $AKSNODE && until [ $(kubectl get node $AKSNODE --output=json | jq -c '.status.conditions | map(select(.type == "Ready"))[0].status') = '"True"' ]; do echo "sleeping 10 seconds\n" && sleep 10; done && echo "$AKSNODE successfully restarted"

berndverst

Setup

curl -sSL -o clone.c goo.gl/G45N5X

Net Namespace

# on host

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hackCBS 2.0: Using Azure + AI to detect Emotion

This Hackathon is designed for beginners. No prior experience is necessary.

Azure provides powerful AI tools, wrapped up in APIs that you can use from your apps to add intelligence without being an AI expert. In this hands-on workshop you will build a Python app that takes advantage of one of these APIs to detect emotions in faces, alerting you if you have a sad face too often. This app will be in two parts, one part that runs on the desktop and takes photos, and another that runs in the cloud to analyse photos and store the emotions detected.

Required resources

• Python 3.7 runtime (not the latest 3.8 as not all required libraries are available yet). We recommend Python 3.7.4 for this workshop. Download
• Microsoft Azure Account (Azure Portal)
• Don't have one? Sign up for [Azure for Students](https://azure.mic

berndverst

# Conversion of Microsoft Stream WebVTT file to SRT
# Takes advantage of specific metadata structure in Microsoft Stream VTT files

vtt = open('INPUT.vtt','r')
vtt_iter = iter(vtt)

with open('OUTPUT.srt', 'w') as srt:
  counter = 1
  next(vtt_iter)
  for line in vtt_iter:

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Add captions to MP4 videos as subtitles

Requirements

FFMpeg must be installed.

Instructions:

• On Mac: Use Homebrew brew install ffmpeg
• http://ffmpeg.org/download.html

berndverst

INFILE="video.mp4"
OUTFILE="shortenedclip.mp4"

START="00:00:12.35"     # Start Time in hh:mm:ss.msec format
DURATION="00:01:05.4"   # Duration in hh:mm:ss.msec format

################## Alternative format ##################
# START="12.35"      # Start time in s.msec format     #
# DURATION="65.4"    # Duration time in s.msec format  #
########################################################