Ariel Patino blackymetal

Based on http://bl.ocks.org/mbostock/899711 which uses D3 to draw elements into a google maps overlay layer, but doesn't use d3.geo machinery to draw map geometry. This gist illustrates how to align a D3 mercator projection with google maps so we can do standard d3 mapping stuff on top of the google API.

Install ImageMagick for image conversion:

brew install imagemagick

Install tesseract for OCR:

brew install tesseract --all-languages

Or install without --all-languages and install them manually as needed.

(a gist based on the old toolmantim article on setting up remote repos)

To collaborate in a distributed development process you’ll need to push code to remotely accessible repositories.

This is somewhat of a follow-up to the previous article setting up a new rails app with git.

For the impatient

Set up the new bare repo on the server:

	var express = require('express');
	var fs = require('fs');
	var Busboy = require('busboy');
	var mime = require('mime');
	var tesseract = require('node-tesseract');

	var app = express();

	app.post('/upload', function(req, res) {
	try {

	import UIKit
	import Foundation
	import XCPlayground

	XCPSetExecutionShouldContinueIndefinitely()

	class RemoteAPI {
	func getData(completionHandler: ((NSArray!, NSError!) -> Void)!) -> Void {
	let url: NSURL = NSURL(string: "http://itunes.apple.com/search?term=Turistforeningen&media=software")
	let ses = NSURLSession.sharedSession()

	# Install linux update, followed by GCC and Make
	sudo yum -y update
	sudo yum install -y gcc make

	# Install Nginx and PHP-FPM
	sudo yum install -y nginx php-fpm

	# Install PHP extensions
	sudo yum install -y php-devel php-mysql php-pdo \
	php-pear php-mbstring php-cli php-odbc \

	# -- Conf --
	[color]
	branch = auto
	diff = auto
	status = auto
	showbranch = auto
	ui = true

	# color.branch
	# A boolean to enable/disable color in the output of git-branch(1). May be set to always, false (or

	'''
	A hack based on this http://mikepultz.com/2011/03/accessing-google-speech-api-chrome-11/. While with smaller voice samples google speech to text works really good, as length increases quality decreases. So here using audiolab and numPy we are breaking audio sample, in smaller chunks, and removing blank/empty spaces from audio signal and then pushing them to google for processing.
	It takes wav file format as input but can be changed to other formats too.
	'''

	from scikits.audiolab import wavread, play, flacwrite
	from numpy import average, array, hstack
	import os
	import sys