Keith Webber townie

This face-boxer.py script is more-or-less the same code that you'll find in the OpenCV tutorial: Face Detection using Haar Cascades. For another variation, with more explanation, check out RealPython's tutorial.

Usage

The face-boxer.py script is designed to be run from the command-line. It has two required arugments:

The path to a XML file containing a Haar-cascade of visual features. In this example, it will be the features that make up a face.
The path to an image file that you want to perform face-detection on. You can pass in more than one image file as space-separated arguments.


	########################
	## Variables
	########################

	variable "environment_name" {
	description = "The name of the environment"
	}

	variable "vpc_id" {

	email = InboudEmail(from="keith@email", body="HIIII PANDA")
	contact_form_email = EmailToContact(email)
	contact_from_email.


	class EmailToContact {
	public static Contact findOrBuildContact(String email_address) {
	Contact result = "Select * from contact where email = email_Address"

	if result == Empty {} // Null,[],empty AKA no match found

	String info = 'Starting Program';

	// SOQL query to load data into object(s)

	// Load ALL books into the list of books
	List<Book__c> books = [SELECT Price__c, Name From Book__c];

	// Load only 1 book into a single book object
	Book__c book = [SELECT Price__c, Name From Book__c limit 1];

	#!/usr/bin/python

	# csv_parser.py - read csv check if shit is present
	# Usage:
	# python csv_parser.py <file.csv>
	# CONFIGURE THESE 2 value
	# postion_of_cig = 2
	# value_of_cig_in_string = '1'
	#
	#

	# This is designed to be a dummy email that will satisfy our SSO's requirement
	# for an email, yet still be canonical to the Datto partner
	def self.convert_username_to_email(username)
	"#{username}@datto.zzz"
	end

	import os
	import hashlib
	from sets import Set

	hash_set = Set([])
	for dirpath, dir, files in os.walk("."):
	files

	hasher = hashlib.md5()
	for file in files:

	"""
	Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
	BSD License
	"""
	import numpy as np

	# data I/O
	data = open('input.txt', 'r').read() # should be simple plain text file
	chars = list(set(data))
	data_size, vocab_size = len(data), len(chars)

	ds_bos_mysql_tutorial_Keith_and_Pam

	What customers are from the UK
	What is the name of the customer who has the most orders?
	What supplier has the highest average product price?
	What category has the most orders?

	5. What employee made the most sales (by number of sales)?
	** 6. What employee made the most sales (by value of sales)?