npinto

import cv2
import cv2.cv as cv


def detect(img, cascade_fn='haarcascades/haarcascade_frontalface_alt.xml',
           scaleFactor=1.3, minNeighbors=4, minSize=(20, 20),
           flags=cv.CV_HAAR_SCALE_IMAGE):

    cascade = cv2.CascadeClassifier(cascade_fn)
    rects = cascade.detectMultiScale(img, scaleFactor=scaleFactor,

heisters

// This code is modified from the working version to remove coupling with the original
// application, and hasn't been tested in its new form. So, it's enough to give you
// the basic idea, but may not entirely work ;)
//
// It assumes the src image is in HSV and the dst image is grayscale.
//
//    CvScalar red = cvScalar(179, 255, 255);
//    CvScalar lowOffset = cvScalar(-20, -150, -150); // find colors down to h = 159, s = 105, v = 105
//    CvScalar highOffset = cvScalar(20, 0, 0); // find colors up to h = 19, s = 255, v = 255 (h wraps/is mod 179)
//    colorThreshold(img, thresholded, red, lowOffset, highOffset);

adammw

Node.js for Raspberry Pi

Pre-built binaries

Recent releases have been pre-built using cross-compilers and this script and are downloadable below.

If you have found these packages useful, give me a shout out on twitter: @adammw

scttnlsn

Pub/sub with MongoDB and Node.js

Setup:

$ mongo
> use pubsub
> db.createCollection('messages', { capped: true, size: 100000 })
> db.messages.insert({})

turtlesoupy

 http {
    proxy_cache_path  /var/cache/nginx levels=1:2 keys_zone=one:8m max_size=3000m inactive=600m;
    proxy_temp_path /var/tmp;
    include       mime.types;
    default_type  application/octet-stream;
    sendfile        on;
    keepalive_timeout  65;

    gzip on;
    gzip_comp_level 6;

nf

var cluster = require('cluster');
var http = require('http');
var numCPUs = require('os').cpus().length;

if (cluster.isMaster) {
  // Fork workers.
  for (var i = 0; i < numCPUs; i++) {
    cluster.fork();
  }
  cluster.on('exit', function(worker, code, signal) {

InternetExplorer

function scoreboardProjection(frame_offset) {

    if (frame_offset == null) frame_offset = 0;
    var canvas, proj;
    var score_img_1,
        score_img_2,
        overlay,
        board_canvas,
        score_canvas_1,
        score_canvas_2;

founddrama

// node:
var moment = require('moment');

moment().add('days', 2).fromNow();
// 'in 2 days'

moment().subtract('days', 2).fromNow();
// '2 days ago'

moment('November 1977').fromNow()

youtalk

// Server-side
app.get('/keyword/search',
        function (req, res, next) {
          var query = new RegExp('^' + req.query.q + '.*$', 'i');
          var result = [];
          mongodb.keywords.find(
            { word: query }, [ 'word' ], { limit: 5 },
            function (err, keywords) {
              keywords.forEach(function (k) {
                result.push(k.word);

Rob-ot

return View.extend({
	initialize: function () {
		this.el.attr("draggable", "true")
		this.el.bind("dragstart", _.bind(this._dragStartEvent, this))
	},

	_dragStartEvent: function (e) {
		var data
		if (e.originalEvent) e = e.originalEvent
		e.dataTransfer.effectAllowed = "copy" // default to copy