Justasic

#include <iostream>
#include <functional>
#include <queue>
// These includes are for later experimentation
#include <thread>
#include <atomic>

std::queue<std::function<void()>> funcs;

Flet

[
{ "keys": ["f12"], "command": "htmlprettify"},
{ "keys": ["f1"], "command": "fold" },
{ "keys": ["f2"], "command": "unfold" },
{ "keys": ["ctrl+l"], "command": "show_overlay", "args": {"overlay": "goto", "text": "@"} },

{ "keys": ["ctrl+space"], "command": "auto_complete" },
{ "keys": ["ctrl+space"], "command": "replace_completion_with_auto_complete", "context":
[
{ "key": "last_command", "operator": "equal", "operand": "insert_best_completion" },

jayrambhia

import cv2
import numpy as np
import itertools

lk_params = dict( winSize  = (10, 10), 
                  maxLevel = 5, 
                  criteria = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.03))   

feature_params = dict( maxCorners = 3000, 
                       qualityLevel = 0.5,

daien

#!/usr/bin/env python

""" Video stabilization with OpenCV (>=2.3) and Hugin

Adrien Gaidon
INRIA - 2012

TODO: add cropping, clean-up and improve doc-strings
"""

larrykite

Mat  img  =  imread("image.jpg");
Mat  grey;
cvtColor(img,  grey,  CV_BGR2GREY);
Mat  sobelx;
Sobel(grey,  sobelx,  CV_32F,  1,  0);
double  minVal,  maxVal;
minMaxLoc(sobelx,  &minVal,  &maxVal);  //find  minimum  and  maximum  intensities
Mat  draw;
sobelx.convertTo(draw,  CV_8U,  255.0/(maxVal  -  minVal),  -minVal);

stickupkid

WifiManager wifiManager = (WifiManager) getSystemService(WIFI_SERVICE);
WifiInfo wifiInfo = wifiManager.getConnectionInfo();
int ipAddress = wifiInfo.getIpAddress();
String ipString = String.format(“%d.%d.%d.%d”, (ip & 0xff), (ip >> 8 & 0xff), (ip >> 16 & 0xff), (ip >> 24 & 0xff));

asabaylus

/**
 * Convert milliseconds in regular style time
 * @author Asa Baylus
 **/

function convertMilliseconds (ms, p) {

        var pattern = p || "hh:mm:ss",
			arrayPattern = pattern.split(":"),
			clock = [ ],

Eckankar

#!/usr/bin/env python
import random

class Markov:
    def __init__(self, file, size):
        self.size = size
        self.starts = []
        self.cache = {}
        self.file_to_words(file)
        self.parse_words()