Taha Dhiaeddine Amdouni tdamdouni

Additional notes

Original blog post - http://blog.alexellis.io/live-stream-with-docker/

How do I rebuild the image from scratch?

This will take several hours on a Raspberry Pi Zero - but less time on a Pi 2 or Pi 3. You can edit the Dockerfile for a Pi 2/3 and change RUN make to RUN make -j 4 to take advantage of the quad-core processor.

$ git clone https://github.com/alexellis/raspberrypi-youtube-streaming/

Install dlib and face_recognition on a Raspberry Pi

Instructions tested with a Raspberry Pi 2 with an 8GB memory card. Probably also works fine on a Raspberry Pi 3.

Steps

Download the latest Raspbian Jessie Light image. Earlier versions of Raspbian won't work.

Write it to a memory card using Etcher, put the memory card in the RPi and boot it up.

Starting from Jessie or Jessie Lite

curl get.pimoroni.com/phatbeat | bash

Then install VLC:

sudo apt-get install vlc-nox

	'''
	A simple Time Timer Black Theme app made of ShapeNodes.
	<Change Line 123 for seconds or minutes counting>
	<Uncomment Line 129 and fill in your shortcut name to
	automatically run other shortcut you defined
	after timer stopped>
	Odd touch attemps will start the timer
	Even touch attemps will stop the timer
	Stops automatically when the set times passed
	'''

	'''
	A simple Time Timer app made of ShapeNodes.
	<Change Line 120 for seconds or minutes counting>
	<Uncomment Line 126 and fill in your shortcut name to
	automatically run other shortcut you defined
	after timer stopped>
	Odd touch attemps will start the timer
	Even touch attemps will stop the timer
	Stops automatically when the set times passed
	'''


	#! /usr/bin/python
	# Python3 code to print IP addresses and host name of local network
	# to e-ink screen

	import nmap
	import sys
	import socket
	from gpiozero import RGBLED, Button
	import smbus

	#!python3
	import ui
	from collections import OrderedDict

	class MyTableViewDataSource (object):
	def __init__(self, data_dict=None):
	self.data = data_dict

	def section_key(self, section):
	#return self.data.keys()[section]

	# written for pythonista ios app, takes advantage of its library and access to ios twitter login. generates a list of followers who don't follow you back and lets you look at each individually to decide whethee to dispose of them or not. Only works for followers < 5000 amd following < 5000, else rate limits and cursors get imvolved and are icky. could use a real UI.

	import twitter, json, webbrowser, random
	account = twitter.get_all_accounts()[0]
	followers = frozenset(json.loads(twitter.request(account, "https://api.twitter.com/1.1/followers/ids.json", "GET")[1].decode("utf-8"))["ids"])
	ifollow = frozenset(json.loads(twitter.request(account, "https://api.twitter.com/1.1/friends/ids.json", "GET")[1].decode("utf-8"))["ids"])
	not_following_back = list(ifollow.difference(followers))
	def make_url(id):
	return 'https://twitter.com/intent/user?user_id=' + str(id)
	turls = [make_url(id) for id in not_following_back]

	import requests, appex
	from urllib.parse import urlparse
	url = appex.get_url().replace("dl=0", "dl=1")
	r = requests.get(url)
	filename = urlparse(url).path.rpartition("/")[-1].replace(".py", "-downloaded.py")
	with open(filename, "wb") as outfile:
	outfile.write(r.content)
	print("script downloaded as " + filename)

	from ctypes import *
	from ctypes import util

	from objc_util import *

	######################################################################

	# QUARTZ / COREGRAPHICS

	quartz = c