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import sys
import math
import random

"""
Point clustering using Python [http://moderndata.plot.ly/point-clustering-in-python/]

This is an improved version of the KMeans Clustering Algorithmn
Which was originally implemented by 'Ian Danforth'.
[Reference: https://gist.github.com/iandanforth/5862470]

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• type of stop channel to bool, less bytes?
• graceful shutdown of the cron instance

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[{"eventId": "6", "visitor": {"abbreviation": "CHA", "players": [{"playerid": 101107, "lastname": "Williams", "jersey": "2", "firstname": "Marvin", "position": "F"}, {"playerid": 203087, "lastname": "Lamb", "jersey": "3", "firstname": "Jeremy", "position": "G"}, {"playerid": 201587, "lastname": "Batum", "jersey": "5", "firstname": "Nicolas", "position": "G-F"}, {"playerid": 202391, "lastname": "Lin", "jersey": "7", "firstname": "Jeremy", "position": "G"}, {"playerid": 1626151, "lastname": "Harrison", "jersey": "9", "firstname": "Aaron", "position": "G"}, {"playerid": 202689, "lastname": "Walker", "jersey": "15", "firstname": "Kemba", "position": "G"}, {"playerid": 203798, "lastname": "Hairston", "jersey": "19", "firstname": "PJ", "position": "F-G"}, {"playerid": 203148, "lastname": "Roberts", "jersey": "22", "firstname": "Brian", "position": "G"}, {"playerid": 203584, "lastname": "Daniels", "jersey": "30", "firstname": "Troy", "position": "G"}, {"playerid": 203469, "lastname": "Zeller", "jersey": "40", "first

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/*
  Hide radio button (the round disc)
  we will use just the label to create pushbutton effect
*/
input[type=radio] {
	display:none; 
	margin:10px;
}

/*

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document.addEventListener('DOMContentLoaded', function() {
  document.querySelectorAll('label')[0].classList.add('button-press');

  document.addEventListener('click', function(e) {
    var e = e || window.event,
        target = e.target || e.srcElement,
        text = target.textContent || target.innerText;

    if (target.tagName.toLowerCase() == 'label') {
      var labels = document.querySelectorAll("label");

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#
# Setup the Docker repository
#

echo "update apt package index"
sudo apt-get update

echo "allow apt to use HTTPS"
sudo apt-get install \
	apt-transport-https \

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import cv2
import pyautogui

# using a screen size specific region
screen = pyautogui.screenshot(region=(200, 100, 1000, 700))
screen_img_gray = cv2.cvtColor(np.array(screen), cv2.COLOR_RGB2GRAY)

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import cv2
import numpy as np

# load and find the dimension attritbutes of the template image
template_img = cv2.imread('./gray-template.png', 0)
w, h = template_img.shape[::-1]

# OpenCV's template matching method
res_img = cv2.matchTemplate(
    screen2, template_img, cv2.TM_CCOEFF_NORMED

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import pytesseract

image_text = pytesseract.image_to_string(cropped_image)

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from gensim.models.keyedvectors import KeyedVectors

# load local word2vec model
model = KeyedVectors.load_word2vec_format(
    os.getenv('SEMANTRIS_SOLVER_WORD2VEC_PATH'),
    binary=True
)

# list of tuples containing the word and similarity score
associated_word_tuples = model.most_similar(word, topn=20)