- AR.js
- clmtrackr
- OpenCV.js
- TensorFlow.js, you can build your own computer vision technology.
- ML5.js — similar goal to TensorFlow.js, build your own ML to recognize patterns, including computer vision!
- Tracking.js — a component based CV tracking system written in JS, you can write functions that define what features you're looking for
With these instructions, you can test a fully local and private ÐApp. Obviously it's not distributed into the cloud here, so it's more like a .. PApp? But we do simulate the full stack locally, so you can push changes to your hearts content!
- Node.js (
brew install node) - IPFS (
brew install ipfs) - Embark (
npm i -g embark) - TestRPC (
npm i -g ethereumjs-testrpc)
| #!/bin/sh -e | |
| # | |
| # This file belongs in /usr/lib/dhcpcd5/dhcpcd how you get it there is up to you | |
| # | |
| DHCPCD=/sbin/dhcpcd | |
| INTERFACES=/etc/network/interfaces | |
| REGEX="^[[:space:]]*iface[[:space:]](*.*)[[:space:]]*inet[[:space:]]*(dhcp|static)" | |
| EXCLUDES="" |
This is a step-by-step tutorial for hosting your website under your domain on IPFS, from zero, on a DigitalOcean Ubuntu 16.04.3 x64 Droplet (i am using the $10 variant with 2GB RAM).
Log in as root.
First, make sure the system is up to date, and install tar and wget:
| function promiseMap(inputValues, mapper) { | |
| const reducer = (acc$, inputValue) => | |
| acc$.then(acc => mapper(inputValue).then(result => acc.push(result) && acc)); | |
| return inputValues.reduce(reducer, Promise.resolve([])); | |
| } | |
| /* Example */ | |
| const axios = require('axios'); |
| // Upgrade NOTE: replaced 'mul(UNITY_MATRIX_MVP,*)' with 'UnityObjectToClipPos(*)' | |
| Shader "Custom/fakeRefract" { | |
| Properties { | |
| } |
| // Iterated from: https://stackoverflow.com/questions/10599933/convert-long-number-into-abbreviated-string-in-javascript-with-a-special-shortn | |
| function abbreviateNumber(value) { | |
| let newValue = value; | |
| const suffixes = ["", "K", "M", "B","T"]; | |
| let suffixNum = 0; | |
| while (newValue >= 1000) { | |
| newValue /= 1000; | |
| suffixNum++; | |
| } |
There are a few problems with delivering alerts via SMS, but they mostly boil down to this: SMS is not very private.
For vulnerable audiences, it’s preferable to not collect any subscriber information at all. This isn’t possible with SMS, because you have to know the recipient’s phone number to deliver a message. Unless you’re talking about burners—which most people won’t have—that phone number is tied to a real identity. This is a vulnerability in at least these scenarios:
- If the alerting app itself gets targeted (whether by LE or other malicious actors), user-identifying information could be leaked.
- Phone companies cooperate with LE, through legal process (subpoenas) or otherwise, to find out which phone subscribers are receiving SMS alerts.
- LE , IC, or well-resourced hackers snoop on the SMS network.
These are the instructions for getting the debugger.html project to connect to and debug Safari on various platforms.
Requirements
- Xcode
- Download and install Xcode from Apple
| function asyncFunc(e) { | |
| return new Promise((resolve, reject) => { | |
| setTimeout(() => resolve(e), e * 1000); | |
| }); | |
| } | |
| const arr = [1, 2, 3]; | |
| let final = []; | |
| function workMyCollection(arr) { |