calebrob6

sudo dpkg-reconfigure --frontend noninteractive tzdata
sudo killall unity-panel-service

calebrob6

import sys
import json
from collections import defaultdict

f = open("stopwords.txt","r")
stopwords = []
for line in f:
    stopwords.append(line.strip())
f.close()

calebrob6

def filterLines(lines):
    size = 4

    for x,y  in lines:
        if x>16 or y>16:
            size = 5

    ignored = []
    for x,y in lines:
        if x==0: ignored.append(y)

calebrob6

import sys

excersiseCards = {
    "a":[50,"jumping jacks"],
    "b":[20,"crunches"],
    "c":[30,"squats"],
    "d":[15,"pushups"],
    "e":[60,"wall sit"],
    "f":[10,"burpees"],
    "g":[20,"arm circles"],

calebrob6

import sys
from multiprocessing import Pool

excersiseCards = {
    "a":[50,"jumping jacks"],
    "b":[20,"crunches"],
    "c":[30,"squats"],
    "d":[15,"pushups"],
    "e":[60,"wall sit"],

calebrob6

#!/usr/bin/env python
import sys,os
import time
import argparse

import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt

import numpy as np

calebrob6

'''
Using data from here http://pjreddie.com/projects/mnist-in-csv/
-- Each row is: label, comma seperated version of 28*28 greyscale image

Good example: http://scikit-learn.org/stable/auto_examples/classification/plot_digits_classification.html#example-classification-plot-digits-classification-py
'''

import numpy as np

calebrob6

import sys
import os
import time

import cv2
import numpy as np


def getOutline(img):

calebrob6

%matplotlib inline
import sys
import os
import time
import warnings
#warnings.filterwarnings("ignore")
#with warnings.catch_warnings():
#    warnings.simplefilter("ignore")

import matplotlib as mpl

calebrob6

#! /usr/bin/env python
# -*- coding: utf-8 -*-
# vim:fenc=utf-8
#
# Copyright © %YEAR% %USER% <%MAIL%>
#
# Distributed under terms of the %LICENSE% license.

import sys
import time