antlypls

guard 'process', :name => 'shrink-images', :command => 'ruby resize-mobile-images.rb mobileretina' do
  watch /^images\/mobileretina\/.+/
end

antlypls

@mixin mobile_bg($file){
  background-image: image-url('mobile/standard/#{$file}');

  @media screen and (-webkit-min-device-pixel-ratio: 2) {
    background-image: image-url('mobile/retina/#{$file}');
    background-size: image-width('mobile/standard/#{$file}') image-height('mobile/standard/#{$file}');
  }
}

// Usage

antlypls

require 'spec/support/grep_matcher'

describe do
  disallow_presence_of pattern: "send(.*#",
    location: "app/",
    description: "Do not use dynamic method invocations",
    failure: "Please change dynamic method call to something more sane."
end

antlypls

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

antlypls

#!/bin/bash

FILE=$(echo $1 | sed 's/.pdf//')

echo "$ pdfcrop $FILE.pdf --margins 12"
pdfcrop $FILE.pdf --margins 12

echo "$ pdftops $FILE-crop.pdf"
pdftops $FILE-crop.pdf

antlypls

#!/bin/bash

if [ -z "$1" ] ; then
  echo 'Project name is empty'
  exit 1
fi

PROJECT_NAME="$1"
SCALA_VERSION="${2-2.11.8}"
SCALATEST_VERSION="${3-2.2.6}"