lxe

For something like https://www.instagram.com/holosomnia/

• 768 x 1024
• High guidance scale 18k and above,
• 200-250 steps,
• 4000+ tv scale,
• lower range scale to 80,
• higher sat scale 2000+,

connorbell

from tkinter import *
from PIL import ImageTk,Image
import time
import os

targetImageWidth = 850
targetImageHeight = 400

inputImageWidth = 0
inputImageHeight = 0

rolux

# git clone https://github.com/NVlabs/stylegan2
import os
import numpy as np
from scipy.interpolate import interp1d
from scipy.io import wavfile
import matplotlib.pyplot as plt
import PIL.Image
import moviepy.editor

import dnnlib

willprice

Kinetics Numeric/String labels

These are mapping files that go between class IDs to class names. These are generated from the training CSV files from each dataset by collecting the unique classes, sorting them, and then numbering them from 0 upwards.

Bleuje

int[][] result;
float t, c;

float ease(float p) {
  return 3*p*p - 2*p*p*p;
}

float ease(float p, float g) {
  if (p < 0.5) 
    return 0.5 * pow(2*p, g);

Bleuje

// Plane folding
// Copyright by tsulej 2014, edited by Etienne Jacob (necessary-disorder.tumblr.com)
// click mouse to change drawing
float step ;
Folds f;

int[] folds = new int[8]; 
 
void setup() {
  size(500, 500);

daz

ffmpeg -f lavfi -i anullsrc=r=11025:cl=mono -t <number of seconds> -acodec aac out.m4a

victor-shepardson

Code

https://gist.github.com/victor-shepardson/5b3d3087dc2b4817b9bffdb8e87a57c4

Setup

I'm using Ubuntu 16.04 with a GTX 1060

install CUDA

genekogan

from bs4 import BeautifulSoup
import requests
import re
import urllib2
import os
import argparse
import sys
import json

# adapted from http://stackoverflow.com/questions/20716842/python-download-images-from-google-image-search

JonnoFTW

from PIL import Image
import numpy as np
import pyprind
import random
import os
import pygame
from collections import defaultdict, Counter


class MarkovChain(object):