cdiener

import sys; from PIL import Image; import numpy as np

chars = np.asarray(list(' .,:;irsXA253hMHGS#9B&@'))

if len(sys.argv) != 4: print( 'Usage: ./asciinator.py image scale factor' ); sys.exit()
f, SC, GCF, WCF = sys.argv[1], float(sys.argv[2]), float(sys.argv[3]), 7/4

img = Image.open(f)
S = ( round(img.size[0]*SC*WCF), round(img.size[1]*SC) )
img = np.sum( np.asarray( img.resize(S) ), axis=2)

Fishrock123

var gulp = require('gulp')

var browserify = require('browserify')
var watchify = require('watchify')
var babelify = require('babelify')

var source = require('vinyl-source-stream')
var buffer = require('vinyl-buffer')
var merge = require('utils-merge')

smajda

/*
 * Directory structure:
 *
 * project/
 *        package.json
 *        gulpfile.js
 *        node_modules/
 *        src/
 *        dist/
 *

soldni

How to install OpenBLAS & multi-threaded Numpy on RedHat

(main source; other info; even more help)

Step 1: make sure to have gfortran installed

Step 2: clone the OpenBLAS repo.

git clone https://github.com/xianyi/OpenBLAS

emiloberg

import React from 'react';
import { Sector, Cell, PieChart, Pie } from 'recharts';

const GaugeChart = () => {
        const width = 500;
        const chartValue = 180;
        const colorData = [{
                value: 40, // Meaning span is 0 to 40
                color: '#663399'
            }, {

pelson

shmerl

#!/bin/bash

# Notes:
#
# 1. Works for tags and specific hash commits too (override mesa_branch variable with needed value).
#
# 2. By default builds for /opt/mesa-<branch> and places the result in ${HOME}/mnt/vmshare/mesa-<branch>
#    You can override the build deployment location by setting dest_dir. For example this should put it right away
#    in /opt/mesa-<branch>
#

jamespo

#!/usr/bin/env python3
# -*- coding: utf-8 -*-

# You'll need a TLS terminating proxy (apache,nginx) in front of this

# This is a simple Hello World Alexa Skill, built using
# the decorators approach in skill builder.
import logging

from flask import Flask