Frederik De Bleser fdb

## weird_shader.glsl
const int STEPS = 512;
const float EPSILON = 0.001;
const float MAX_DIST = 20.;

vec3 palette( in float t, in vec3 a, in vec3 b, in vec3 c, in vec3 d )
{
    return a + b*cos( 6.28318*(c*t+d) );
}

float sdOctahedron( vec3 p, float s)

## the-force-fbm-test.frag
// Simple shader that I created for a shader workshop by Char Stiles
// https://codame.com/events/workshop-shaders

// Copy-paste this code in The Force:
// https://shawnlawson.github.io/The_Force/
// It needs music to shine! Works well with Azuki:
// https://soundcloud.com/azuki/sets/inverness
// (In The Force, click the microphone icon at the bottom, choose SoundCloud, paste the URL and press load.)

float circ(vec2 position){

## setup_nvidia_docker.sh
#!/bin/bash

# This script is used to setup a working Tensorflow GPU installation using Docker.
# It's only tested on Ubuntu 18.04.
# When all is done, run the following command to get a Bash shell with Tensorflow:
# docker run --gpus all -u $(id -u):$(id -g) -v $PWD:/root -it --rm tensorflow/tensorflow:latest-gpu-py3 bash

# Setup Docker
# Instructions from https://docs.docker.com/install/linux/docker-ce/ubuntu/

## pushing.js
// Use in http://sketch.paperjs.org/

function rand(min, max) {
    return min + Math.random() * (max - min);
}

var RADIUS = 400;

var circ = new Path.Circle({
    position: view.center,

## count_words.py
import csv
import string

translator = str.maketrans('', '', string.punctuation)

word_count = {}
text = open('declaration.txt').read()

words = text.split()
for word in words:

## Cargo.toml
[package]
name = "procaddress"
version = "0.1.0"
authors = []

[dependencies]
libc = "0.2.33"

## Cargo.toml
[package]
name = "procaddress"
version = "0.1.0"
authors = []

[dependencies]
libc = "0.2.33"

## Cargo.toml
[package]
name = "vec"
version = "0.1.0"
authors = ["Frederik De Bleser <frederik@debleser.be>"]

[lib]
name = "vec"
crate-type = ["dylib"]

[dependencies]

## index.html
<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8">
  <script src="https://cdn.rawgit.com/Caligatio/jsSHA/v2.2.0/src/sha256.js"></script>
  <title>S3 Post Upload Example</title>
  <style>
    body { font: 14px arial; padding: 20px; margin: 80px auto; width: 40rem; }
    input { display: block; font: 16px arial; padding: 5px; margin: 5px; width: 40rem;}
  </style>

## random-letter.py
# NodeBox 1 script that generates a composition of random letters.
# Download NodeBox 1 at https://www.nodebox.net/download/
size(800, 400)
from random import choice, uniform, seed
seed(52)

colors = [[0, 0, 0], [1, 0, 0], [1, 1, 1]]

def comp(x, y, w, h):
    push()
	const int STEPS = 512;
	const float EPSILON = 0.001;
	const float MAX_DIST = 20.;

	vec3 palette( in float t, in vec3 a, in vec3 b, in vec3 c, in vec3 d )
	{
	return a + bcos( 6.28318(c*t+d) );
	}

	float sdOctahedron( vec3 p, float s)
	// Simple shader that I created for a shader workshop by Char Stiles
	// https://codame.com/events/workshop-shaders

	// Copy-paste this code in The Force:
	// https://shawnlawson.github.io/The_Force/
	// It needs music to shine! Works well with Azuki:
	// https://soundcloud.com/azuki/sets/inverness
	// (In The Force, click the microphone icon at the bottom, choose SoundCloud, paste the URL and press load.)

	float circ(vec2 position){
	#!/bin/bash

	# This script is used to setup a working Tensorflow GPU installation using Docker.
	# It's only tested on Ubuntu 18.04.
	# When all is done, run the following command to get a Bash shell with Tensorflow:
	# docker run --gpus all -u $(id -u):$(id -g) -v $PWD:/root -it --rm tensorflow/tensorflow:latest-gpu-py3 bash

	# Setup Docker
	# Instructions from https://docs.docker.com/install/linux/docker-ce/ubuntu/
	// Use in http://sketch.paperjs.org/

	function rand(min, max) {
	return min + Math.random() * (max - min);
	}

	var RADIUS = 400;

	var circ = new Path.Circle({
	position: view.center,
	import csv
	import string

	translator = str.maketrans('', '', string.punctuation)

	word_count = {}
	text = open('declaration.txt').read()

	words = text.split()
	for word in words:
	[package]
	name = "procaddress"
	version = "0.1.0"
	authors = []

	[dependencies]
	libc = "0.2.33"
	[package]
	name = "vec"
	version = "0.1.0"
	authors = ["Frederik De Bleser <frederik@debleser.be>"]

	[lib]
	name = "vec"
	crate-type = ["dylib"]

	[dependencies]
	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="UTF-8">
	<script src="https://cdn.rawgit.com/Caligatio/jsSHA/v2.2.0/src/sha256.js"></script>
	<title>S3 Post Upload Example</title>
	<style>
	body { font: 14px arial; padding: 20px; margin: 80px auto; width: 40rem; }
	input { display: block; font: 16px arial; padding: 5px; margin: 5px; width: 40rem;}
	</style>
	# NodeBox 1 script that generates a composition of random letters.
	# Download NodeBox 1 at https://www.nodebox.net/download/
	size(800, 400)
	from random import choice, uniform, seed
	seed(52)

	colors = [[0, 0, 0], [1, 0, 0], [1, 1, 1]]

	def comp(x, y, w, h):
	push()