yohannawaliya

#!/usr/bin/env python

import csv
from xml.etree import ElementTree
from langdetect import detect_langs
from requests_html import HTMLSession

http = HTMLSession()

def langs(url):

yohannawaliya

import tweepy
import csv
import pandas as pd
####input your credentials here
consumer_key = ''
consumer_secret = ''
access_token = ''
access_token_secret = ''

auth = tweepy.OAuthHandler(consumer_key, consumer_secret)

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{
	"origin": [
		"<svg width=\"400\" height=\"200\">#pattern#</svg>"
	],
	"circlecolor": [
		"pink",
		"cyan",
		"yellow",
		"orange",
		"gray",

yohannawaliya

/*
  A simple Twitter bot that posts random images.
  Tutorial: https://botwiki.org/resource/tutorial/random-image-tweet/
*/

const fs = require( 'fs' ),
      path = require( 'path' ),
      Twit = require( 'twit' ),
      config = require( path.join( __dirname, 'config.js' ) ),
      images = require( path.join( __dirname, 'images.js' ) );

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This is free and unencumbered software released into the public domain.

Anyone is free to copy, modify, publish, use, compile, sell, or
distribute this software, either in source code form or as a compiled
binary, for any purpose, commercial or non-commercial, and by any
means.

In jurisdictions that recognize copyright laws, the author or authors
of this software dedicate any and all copyright interest in the
software to the public domain. We make this dedication for the benefit

yohannawaliya

Gil Levi and Tal Hassner, Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns

Convolutional neural networks for emotion classification from facial images as described in the following work:

Gil Levi and Tal Hassner, Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns, Proc. ACM International Conference on Multimodal Interaction (ICMI), Seattle, Nov. 2015

Project page: http://www.openu.ac.il/home/hassner/projects/cnn_emotions/

If you find our models useful, please add suitable reference to our paper in your work.