William Ratcliff williamratcliff

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Speech recognition demo by ggulati

Original https://gist.github.com/GGulati/1ebaeaaa7f7408647fef via https://ggulati.wordpress.com/2016/02/24/coding-jarvis-in-python-3-in-2016/ via https://news.ycombinator.com/item?id=11172727

I did some modifications to try to get it to work on Mac OS.

Install

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

	#!/bin/env python

	"""
	Simple VTK example in Python to load an STL mesh and display with a manipulator.
	Chris Hodapp, 2014-01-28, (c) 2014
	"""

	import vtk

	def render():

	NUMBERS_SET = 'numbers'
	TWILIO_NUMBER = '+12345678900'
	TWILIO_SID = 'account_sid'
	TWILIO_TOKEN = 'auth_token'

	express = require('express')
	http = require('http')
	path = require('path')
	redis = require('redis')
	app = express()

	import speech_recognition
	import pyttsx

	speech_engine = pyttsx.init('sapi5') # see http://pyttsx.readthedocs.org/en/latest/engine.html#pyttsx.init
	speech_engine.setProperty('rate', 150)

	def speak(text):
	speech_engine.say(text)
	speech_engine.runAndWait()