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Tesseract.js

npm version

Tesseract.js is a javascript library that gets words in almost any language out of images. (Demo)

fancy demo gif

Tesseract.js works with script tags, webpack/browserify, and node. After you install it, using it is as simple as

Tesseract.recognize(myImage)
         .progress(function  (p) { console.log('progress', p)    })
         .then(function (result) { console.log('result', result) })

Check out the docs for a full treatment of the API.

Installation

Tesseract.js works with a <script> tag via local copy or cdn, with webpack and browserify via npm, and on node via npm. Check out the docs for a full treatment of the API.

<script />

You can simply include Tesseract.js with a cdn like this:

<script src='https://cdn.rawgit.com/naptha/tesseract.js/0.2.0/dist/tesseract.js'></script>

After including your scripts, the Tesseract variable should be defined! You can head to the docs for a full treatment of the API.

npm

First:

> npm install tesseract.js --save

Then

var Tesseract = require('tesseract.js')

or

import Tesseract from 'tesseract.js'

You can head to the docs for a full treatment of the API.

Docs

Tesseract.recognize(image: ImageLike[, options]) -> TesseractJob

Figures out what words are in image, where the words are in image, etc.

Note: image should be be sufficiently high resolution. Often, the same image will get much better results if you upscale it before calling recognize.

Returns a TesseractJob whose then, progress, and catch methods can be used to act on the result.

Simple Example:

Tesseract.recognize(myImage)
.then(function(result){
    console.log(result)
})

More Complicated Example:

// if we know our image is of spanish words without the letter 'e':
Tesseract.recognize(myImage, {
    lang: 'spa',
    tessedit_char_blacklist: 'e'
})
.then(function(result){
    console.log(result)
})

Tesseract.detect(image: ImageLike) -> TesseractJob

Figures out what script (e.g. 'Latin', 'Chinese') the words in image are written in.

Returns a TesseractJob whose then, progress, and error methods can be used to act on the result of the script.

Tesseract.detect(myImage)
.then(function(result){
    console.log(result)
})

ImageLike

The main Tesseract.js functions take an image parameter, which should be something that is like an image. What's considered "image-like" differs depending on whether it is being run from the browser or through NodeJS.

On a browser, an image can be:

  • an img, video, or canvas element
  • a CanvasRenderingContext2D (returned by canvas.getContext('2d'))
  • a File object (from a file <input> or drag-drop event)
  • a Blob object
  • a ImageData instance (an object containing width, height and data properties)
  • a path or URL to an accessible image (the image must either be hosted locally or accessible by CORS)

In NodeJS, an image can be

  • a path to a local image
  • a Buffer instance containing a PNG or JPEG image
  • a ImageData instance (an object containing width, height and data properties)

TesseractJob

A TesseractJob is an an object returned by a call to recognize or detect. It's inspired by the ES6 Promise interface and provides then and catch methods. One important difference is that these methods return the job itself (to enable chaining) rather than new.

Typical use is:

Tesseract.recognize(myImage)
    .progress(function(message){console.log(message)})
    .catch(function(err){console.error(err)})
    .then(function(result){console.log(result)})

Which is equivalent to:

var job1 = Tesseract.recognize(myImage);

job1.progress(function(message){console.log(message)});

job1.catch(function(err){console.error(err)});

job1.then(function(result){console.log(result)})

TesseractJob.progress(callback: function) -> TesseractJob

Sets callback as the function that will be called every time the job progresses.

  • callback is a function with the signature callback(progress) where progress is a json object.

For example:

Tesseract.recognize(myImage)
    .progress(function(message){console.log('progress is: ', message)})

The console will show something like:

progress is: {loaded_lang_model: "eng", from_cache: true}
progress is: {initialized_with_lang: "eng"}
progress is: {set_variable: Object}
progress is: {set_variable: Object}
progress is: {recognized: 0}
progress is: {recognized: 0.3}
progress is: {recognized: 0.6}
progress is: {recognized: 0.9}
progress is: {recognized: 1}

TesseractJob.then(callback: function) -> TesseractJob

Sets callback as the function that will be called if and when the job successfully completes.

  • callback is a function with the signature callback(result) where result is a json object.

For example:

Tesseract.recognize(myImage)
    .then(function(result){console.log('result is: ', result)})

The console will show something like:

progress is: {
    blocks: Array[1]
    confidence: 87
    html: "<div class='ocr_page' id='page_1' ..."
    lines: Array[3]
    oem: "DEFAULT"
    paragraphs: Array[1]
    psm: "SINGLE_BLOCK"
    symbols: Array[33]
    text: "Hello World↵from beyond↵the Cosmic Void↵↵"
    version: "3.04.00"
    words: Array[7]
}

TesseractJob.catch(callback: function) -> TesseractJob

Sets callback as the function that will be called if the job fails.

  • callback is a function with the signature callback(erros) where error is a json object.

Local Installation

In the browser, tesseract.js simply provides the API layer. Internally, it opens a WebWorker to handle requests. That worker itself loads code from the Emscripten-built tesseract.js-core which itself is hosted on a CDN. Then it dynamically loads language files hosted on another CDN.

Because of this we recommend loading tesseract.js from a CDN. But if you really need to have all your files local, you can use the Tesseract.create function which allows you to specify custom paths for workers, languages, and core.

window.Tesseract = Tesseract.create({
    workerPath: '/path/to/worker.js',
    langPath: 'https://cdn.rawgit.com/naptha/tessdata/gh-pages/3.02/',
    corePath: 'https://cdn.rawgit.com/naptha/tesseract.js-core/0.1.0/index.js',
})

corePath

A string specifying the location of the tesseract.js-core library, with default value 'https://cdn.rawgit.com/naptha/tesseract.js-core/master/index.js'. Set this string before calling Tesseract.recognize and Tesseract.detect if you want Tesseract.js to use a different file.

workerPath

A string specifying the location of the tesseract.worker.js file, with default value 'https://cdn.rawgit.com/naptha/tesseract.js/8b915dc/dist/tesseract.worker.js'. Set this string before calling Tesseract.recognize and Tesseract.detect if you want Tesseract.js to use a different file.

langPath

A string specifying the location of the tesseract language files, with default value 'https://cdn.rawgit.com/naptha/tessdata/gh-pages/3.02/'. Language file urls are calculated according to the formula langPath + langCode + '.traineddata.gz'. Set this string before calling Tesseract.recognize and Tesseract.detect if you want Tesseract.js to use different language files.

Contributing

Development

To run a development copy of tesseract.js, first clone this repo.

> git clone https://github.com/naptha/tesseract.js.git

Then, cd in to the folder, npm install, and npm start

> cd tesseract.js
> npm install && npm start

  ... a bunch of npm stuff ... 

  Starting up http-server, serving ./
  Available on:
    http://127.0.0.1:7355
    http://[your ip]:7355

Then open http://localhost:7355/examples/file-input/demo.html in your favorite browser. The devServer automatically rebuilds tesseract.js and tesseract.worker.js when you change files in the src folder.

Building Static Files

After you've cloned the repo and run npm install as described in the Development Section, you can build static library files in the dist folder with

> npm run build

Send us a Pull Request!

Thanks :)