Jonny Buchanan insin

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

Comparing the proposed loading order of <script type="module"> with the current script tag loading methods. Showing a comparison of HTML parsing, script loading and executing scripts.

Classic (<script>) loading blocks the parser to fetch the code and then blocks again execute the code then goes back to parsing the HTML.
Defer (<script defer>) will not block the parsing to trigger the fetch but it will happen at the same time, the execution of the script will happen after the parsing is complete.
Async (<script async>) will not block the parsing to trigger the fetch but it will block to execute the script, after that has happened it will continue the parsing.
Module (<script type="module">) will behave like defer in that it will fetch in parallel to parsing but also it's dependency tree is fetched at the same time in parallel. After the parsing has completed it will execute the scripts.
Async module (`

The idea of these steps is that they can be implemented progressively and add value at each step.

Your current approach is to talk to REST APIs from your client-side code
Build your GraphQL server
Instead of making multiple REST requests for a page load, make a single GraphQL query
Develop a means of composing GraphQL queries out of fragments. There are a few existing solutions for this, but they're not particularly polished

At this point you have a pretty nice solution for fetching data, but no strategy for caching or semantics surrounding that data. There's also questions surrounding how to minimise data fetching on navigation using client-side routing.

Client-side routing optimisation is potentially straightforward (if you're good at working with trees), but might become impractical depending on how other problems are solved. The basic idea is that you build the query for the current and next routes, convert them to ASTs (this is easy using graphql-js) and create a diff query that only as

Installing Babel

The following are a few important npm packages.

Core Babel and access to Babel:

babel-core: the core compilation machinery and plugin infrastructure for Babel. You will rarely need to install this package, because other packages such as babel-cli have it as a dependency, meaning that it will be automatically installed when they are installed.
babel-cli: a command line interface to Babel. It includes the following commands:
babel-doctor detects common problems with your Babel installation.

	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="UTF-8">
	<title></title>
	</head>
	<body>
	<div id="app-root"></div>
	{{scripts}}
	</body>

	import { combineReducers } from 'redux';
	import users from './reducers/users';
	import posts from './reducers/posts';

	export default function createReducer(asyncReducers) {
	return combineReducers({
	users,
	posts,
	...asyncReducers
	});

	import React, {Component} from 'react';
	import {bindActionCreators} from "redux"
	import { connect } from 'react-redux';
	import {schema, getModelByType} from "models/models"

	import SomeFormComponent from "SomeFormComponent"

	import {selectedItemSelector, isEditingSelector} from "selectors/entities"

	let mapStateToProps = (state) => {

	'use strict';

	const util = require('util');
	const execSync = require('child_process').execSync;

	const ignoreModules = [
	'react-heatpack-script-alias',
	'babel-runtime'
	];

	JedWatson/classnames (2650855 dls, 1465 stars)
	yannickcr/eslint-plugin-react (2077066 dls, 710 stars)
	rackt/react-router (1833204 dls, 9050 stars)
	facebook/react-dom (782024 dls, 33044 stars)
	gaearon/react-hot-loader (708042 dls, 3250 stars)
	rackt/redux (568969 dls, 10743 stars)
	rackt/react-redux (495498 dls, 1509 stars)
	jsdf/coffee-react-transform (463488 dls, 380 stars)
	JedWatson/react-input-autosize (455277 dls, 107 stars)
	reflux/reflux (393281 dls, 4316 stars)

	@namespace url(http://www.w3.org/1999/xhtml);

	@-moz-document domain("twitter.com") {
	/* styles for collapsing media in tweets and showing an arrow to indicate their existence
	but only at the top level */
	ol.stream-items > .expanding-stream-item:not(.open) .OldMedia,
	ol.stream-items > .expanding-stream-item:not(.open) .AdaptiveMedia {
	display: none;
	}