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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

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import Image, ImageDraw

def get_colors(infile, outfile, numcolors=10, swatchsize=20, resize=150):

    image = Image.open(infile)
    image = image.resize((resize, resize))
    result = image.convert('P', palette=Image.ADAPTIVE, colors=numcolors)
    result.putalpha(0)
    colors = result.getcolors(resize*resize)

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# install dependencies
sudo apt-get update
sudo apt-get install -y build-essential
sudo apt-get install -y cmake
sudo apt-get install -y libgtk2.0-dev
sudo apt-get install -y pkg-config
sudo apt-get install -y python-numpy python-dev
sudo apt-get install -y libavcodec-dev libavformat-dev libswscale-dev
sudo apt-get install -y libjpeg-dev libpng-dev libtiff-dev libjasper-dev
 

saibabanadh

var AWS = require('aws-sdk');

AWS.config.update({
  accessKeyId: '{AWS_KEY}',
  secretAccessKey: '{AWS_SECRET}',
  region: '{SNS_REGION}'
});

var sns = new AWS.SNS();

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var winston = require( 'winston' ),
	fs = require( 'fs' ),
	logDir = 'log', // Or read from a configuration
	env = process.env.NODE_ENV || 'development',
	logger;

winston.setLevels( winston.config.npm.levels );
winston.addColors( winston.config.npm.colors );

if ( !fs.existsSync( logDir ) ) {