VIBE | Official implementation of CVPR2020 paper | Computer Vision library

    
DESIGN YOUR OWN VIBE
Type in your message, choose font, and color.







Total Cost:


INPUT TEXT




CHOOSE FONT

-SELECT-
Roboto
Arial
Times New Roman
Comic Sans MS
Clarendon Fortune
Copperplate
Ribbon Condensed


CHOOSE COLOR

-SELECT-
Red
Blue
Green
Orange
Pink
White
Yellow
Ice Blue


CHOOSE SIZE

-SELECT-
20"
30"
40"
50"
60"


CHOOSE POWER WIRE
Power wire on back is recommended for professional installation by an electrician. Power wire on front is recommended for residential installation.

-SELECT-
Power Wire In FRONT
Power Wire In BACK


CHOOSE MOUNT
Wall mount is recommended for general installations. Hanging is recommended for window display.

-SELECT-
Wall Mount
Hanging
Stand


CHOOSE BACKING

-SELECT-
Cut To Shape
Whole Board


DIMMER?

-SELECT-
Yes ($50.00)
No

const BaseCommand = require('../../utils/structures/BaseCommand');
const Discord = require("Discord.js");

module.exports = class VibeCheckCommand extends BaseCommand {
  constructor() {
    super('vibecheck', 'fun', []);
  }

 async run(client, message, args) {
  var rating = Math.floor(Math.random() * 100) + 1;
  let mention = message.mentions.users.first();

  if (!mention) return message.channel.send("Taguj usera prvo!");
  const mentionedMember = message.mentions.members.first();
  const messageToSay = args.join(" ");
  const sayEmbed = new Discord.MessageEmbed()


  message.channel.send(`Au brate ${mention} nisi passo vibe check 😢`, {files: ["https://cdn.discordapp.com/attachments/821106910441898025/822208416906608671/you_out.jpg"]});

  message.channel.send(`MA MAN! VIBEEE ${mention} UPADAJ!`, {files: ["https://cdn.discordapp.com/attachments/821106910441898025/822208425319727114/you_in_.jpg"]});

  }
}

import numpy as np
import pandas as pd
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.naive_bayes import MultinomialNB
from sklearn.metrics import (f1_score,precision_score,recall_score)
ifile=open("train_pos.txt")
rows = []
for ln in ifile:
    rows.append({'text': ln, 'class': 1})
ifile.close()
data_frame = pd.DataFrame(rows)
data_frame