In [1]:

    

import json
import urllib.request
import random
import PIL
import word2vec
import sys
import memegenerator
import twitter_credentials
import scipy.ndimage


    

In [2]:

    

model = word2vec.load('../text8.bin')


    

In [3]:

    

consumer_key = twitter_credentials.consumer_key
consumer_secret = twitter_credentials.consumer_secret
access_token = twitter_credentials.access_token
access_token_secret = twitter_credentials.access_token_secret


    

In [4]:

    

import tweepy

# == OAuth Authentication ==
#
# This mode of authentication is the new preferred way
# of authenticating with Twitter.

auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.secure = True
auth.set_access_token(access_token, access_token_secret)

api = tweepy.API(auth)

# If the authentication was successful, you should
# see the name of the account print out
print(api.me().name)

# If the application settings are set for "Read and Write" then
# this line should tweet out the message to your account's
# timeline. The "Read and Write" setting is on https://dev.twitter.com/apps
# api.update_status(status='Updating using OAuth authentication via Tweepy!')


    

    




Tenn Leeuwenburg

In [5]:

    

public_tweets = api.home_timeline()


    

In [6]:

    

valid_tweets = []
best_tweets = []
for t in public_tweets:
    words = t.text.split()
    words = [w for w in words if w in model.vocab]
    words2 = [w for w in words if len(w) > 3]
    if len(words) < 3:
        continue
        
    if len(words2) >= 3:
        best_tweets.append(t)
        
    valid_tweets.append(t)

tweet = random.choice(public_tweets)
if best_tweets:
    tweet = random.choice(best_tweets)


    

In [7]:

    

words = tweet.text.split()
words2 = [w for w in words if len(w) > 3]
words2 = [w for w in words2 if w in model.vocab]

ws = []
while(len(ws) <= 2):
    
    using = words
    if words2:
        using = words2
    
    w = random.choice(using)
    using.pop(using.index(w))
    if w in model.vocab:
        ws.append(w)


    

In [8]:

    

indexes, metrics = model.analogy(pos=[ws[0], ws[1]], neg=[ws[2]], n=10)


    

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ws.append(model.vocab[indexes][0])


    

In [10]:

    

if using:
    ws.append(using[0])
else:
    ws.append(ws[0])


    

In [11]:

    

print(tweet.text)
print(ws)


    

    




RT @5LiD3: Furiosa and the gang!
more resolutions can be found here
http://t.co/7wGOK6K2Nc
#MadMax #MadMaxFuryRoad http://t.co/sBlE3SHCvj
['more', 'here', 'found', 'less', 'resolutions']

In [12]:

    

url_template = 'https://ajax.googleapis.com/ajax/services/search/images?v=1.0&q=%s&imgsz=xlarge&imgtype=photo&as_sitesearch=flickr.com'
url = url_template % ws[4]
result = urllib.request.urlopen(url)
js = json.loads(result.read().decode())
image_url = js['responseData']['results'][0]['unescapedUrl']

filename = urllib.request.urlretrieve(image_url)[0]
topString = '%s is to %s' % (ws[0], ws[1])
bottomString = "as %s is to %s" % (ws[2], ws[3])
memegenerator.make_meme(topString, bottomString, filename)


    

In [13]:

    

imagename = 'temp.png'
%matplotlib inline


    

In [14]:

    

from PIL import Image
im = Image.open(imagename)
im.show()


    

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