ad8e

/* Note: this Google copyright notice only applies to the original file, which has large sections copy-pasted here. my changes are under CC0 (public domain).

 * Copyright 2015 Google Inc.
 *
 * Use of this source code is governed by a BSD-style license that can be
 * found in the LICENSE file.
 */

/*
The official instructions don't work well. These alternative instructions are intended to be the shortest path to get a minimal setup running.

clungzta

import cv2
import numpy as np

def overlay_transparent(background_img, img_to_overlay_t, x, y, overlay_size=None):
    """
    @brief      Overlays a transparant PNG onto another image using CV2
    
    @param      background_img    The background image
    @param      img_to_overlay_t  The transparent image to overlay (has alpha channel)
    @param      x                 x location to place the top-left corner of our overlay

haavard

This work, excluding the Arch Linux logo, is made available under CC0: https://creativecommons.org/publicdomain/zero/1.0/

agrafix

/**
 * C++ implementation of FFT
 *
 * Source: http://paulbourke.net/miscellaneous/dft/
 */

#pragma once

/*
   This computes an in-place complex-to-complex FFT

kylemcdonald

import numpy as np
import subprocess as sp
import os
DEVNULL = open(os.devnull, 'w')

# load_audio can not detect the input type
def ffmpeg_load_audio(filename, sr=44100, mono=False, normalize=True, in_type=np.int16, out_type=np.float32):
    channels = 1 if mono else 2
    format_strings = {
        np.float64: 'f64le',

patriciogonzalezvivo

Please consider using http://lygia.xyz instead of copy/pasting this functions. It expand suport for voronoi, voronoise, fbm, noise, worley, noise, derivatives and much more, through simple file dependencies. Take a look to https://github.com/patriciogonzalezvivo/lygia/tree/main/generative

Generic 1,2,3 Noise

float rand(float n){return fract(sin(n) * 43758.5453123);}

float noise(float p){
	float fl = floor(p);
  float fc = fract(p);

positlabs

Vignette = function (canvas) {

  var alpha = .7,
		context,
		visible,
		data;

	(function initView() {

		context = canvas.getContext("2d");

ganwell

import numpy
import scipy
import matplotlib.pyplot as pyplot

def decibel(lin):
	"""Convert amplitude to decibel.
	
	We might later need power to decibel..."""
	return 20*numpy.log10(norm(lin))