Falconerd

/**
 * This gulpfile will copy static libraries and a index.html file as well as 
 * merge, babelify and uglify the rest of the javascript project.
 *
 * TODO:
 * - Separate media, libs and src with different watchers.
 * - Media and libs should only be copied to dist if they are different sizes.
 * 
 * The expected project is to be laid out as such:
 *

kdzwinel

/*
This script attempts to identify all CSS classes mentioned in HTML but not defined in the stylesheets.

In order to use it, just run it in the DevTools console (or add it to DevTools Snippets and run it from there).

Note that this script requires browser to support `fetch` and some ES6 features (fat arrow, Promises, Array.from, Set). You can transpile it to ES5 here: https://babeljs.io/repl/ .

Known limitations:
- it won't be able to take into account some external stylesheets (if CORS isn't set up) 
- it will produce false negatives for classes that are mentioned in the comments.

rasmusab

# A Bayesian model that calculates a probability that a couple is fertile 
# and pregnant. Please use this for fun only, not for any serious purpose 
# like *actually* trying to figure out whether you are pregnant.

# Enter your own period onsets here:
period_onset <- as.Date(c("2014-07-02", "2014-08-02", "2014-08-29", "2014-09-25", 
                          "2014-10-24", "2014-11-20", "2014-12-22", "2015-01-19"))
# If you have no dates you can just set days_between_periods to c() instead like:
# days_between_periods <- c()
days_between_periods <- as.numeric(diff(period_onset))

Uchean

Get ClamAV running on Mac OS X (using Homebrew)

The easiest way to get the ClamAV package is using Homebrew

$ brew install clamav

Before trying to start the clamd process, you'll need a copy of the ClamAV databases.

Create a freshclam.conf file and configure as so

arfon

#!/usr/bin/ruby

# For an OO language, this is distinctly procedural. Should probably fix that.
require 'json'

details = Hash.new({})

capture_params = [
  { :name => "title", :message => "Enter project name." },
  { :name => "url", :message => "Enter the URL of the project repository." },

dannguyen

Using Python 3 + Google Cloud Vision API's OCR to extract text from photos and scanned documents

Just a quickie test in Python 3 (using Requests) to see if Google Cloud Vision can be used to effectively OCR a scanned data table and preserve its structure, in the way that products such as ABBYY FineReader can OCR an image and provide Excel-ready output.

The short answer: No. While Cloud Vision provides bounding polygon coordinates in its output, it doesn't provide it at the word or region level, which would be needed to then calculate the data delimiters.

On the other hand, the OCR quality is pretty good, if you just need to identify text anywhere in an image, without regards to its physical coordinates. I've included two examples:

####### 1. A low-resolution photo of road signs

0xjac

The repository for the assignment is public and Github does not allow the creation of private forks for public repositories.

The correct way of creating a private frok by duplicating the repo is documented here.

For this assignment the commands are:

1. Create a bare clone of the repository. (This is temporary and will be removed so just do it wherever.)

git clone --bare [email protected]:usi-systems/easytrace.git

gagarine

Howto Install clamav on OSX with brew

Note: on legacy intel system the path may be /usr/local/etc/clamav instead of /opt/homebrew/etc/clamav/

$ brew install clamav
$ cd /opt/homebrew/etc/clamav/
$ cp freshclam.conf.sample freshclam.conf

joyrexus

collapsible markdown?

CLICK ME

yes, even hidden code blocks!

print("hello world!")

josejimenezluna

import numpy as np
from numpy.linalg import norm, solve
from scipy.spatial.distance import cdist
from sklearn.neighbors import kneighbors_graph


def phi(l, mu):
    return (mu * (np.sqrt(l) - 1)**2)