tesseract.js
Advanced tools
tesseract.js is a JavaScript library that provides Optical Character Recognition (OCR) capabilities. It allows you to extract text from images and PDFs directly in the browser or in a Node.js environment.
Basic OCR
This feature allows you to perform basic OCR on an image file. The code sample demonstrates how to recognize text from an image using the English language.
const Tesseract = require('tesseract.js');
Tesseract.recognize(
'path/to/image.png',
'eng',
{
logger: m => console.log(m)
}
).then(({ data: { text } }) => {
console.log(text);
});Handling Multiple Languages
This feature allows you to recognize text in multiple languages. The code sample demonstrates how to recognize text from an image using both English and Spanish languages.
const Tesseract = require('tesseract.js');
Tesseract.recognize(
'path/to/image.png',
'eng+spa',
{
logger: m => console.log(m)
}
).then(({ data: { text } }) => {
console.log(text);
});Progress Reporting
This feature provides real-time progress updates during the OCR process. The code sample demonstrates how to log progress messages to the console.
const Tesseract = require('tesseract.js');
Tesseract.recognize(
'path/to/image.png',
'eng',
{
logger: m => console.log(m)
}
).then(({ data: { text } }) => {
console.log(text);
});Using Worker for Performance
This feature allows you to use a worker for better performance, especially for large images or multiple OCR tasks. The code sample demonstrates how to create a worker, load the necessary language, perform OCR, and then terminate the worker.
const { createWorker } = require('tesseract.js');
const worker = createWorker({
logger: m => console.log(m)
});
(async () => {
await worker.load();
await worker.loadLanguage('eng');
await worker.initialize('eng');
const { data: { text } } = await worker.recognize('path/to/image.png');
console.log(text);
await worker.terminate();
})();ocrad.js is a JavaScript port of the OCRAD OCR library. It is designed to be used in the browser and can recognize text from images. Compared to tesseract.js, ocrad.js is lighter but may not be as accurate or feature-rich.
node-tesseract-ocr is a Node.js wrapper for the Tesseract OCR engine. It provides a simpler interface for performing OCR in Node.js environments. While it offers similar functionalities to tesseract.js, it does not support browser usage.
Tesseract.js is a javascript library that gets words in almost any language out of images. (Demo)
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.
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.
You can simply include Tesseract.js with a cdn like this:
<script src='https://cdn.rawgit.com/naptha/tesseract.js/1.0.8/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.
First:
> npm install tesseract.js --save
Note: Tesseract.js currently requires node v6.8.0 or greater.
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.
Figures out what words are in image, where the words are in image, etc.
Note:
imageshould be be sufficiently high resolution. Often, the same image will get much better results if you upscale it before callingrecognize.
image is any ImageLike object.options is either absent (in which case it is interpreted as 'eng'), a string specifing a language short code from the language list, or a flat json object that may:
lang property with a value from the list of lang parametersReturns a TesseractJob whose then, progress, catch and finally methods can be used to act on the result.
Tesseract.recognize(myImage)
.then(function(result){
console.log(result)
})
// 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)
})
Figures out what script (e.g. 'Latin', 'Chinese') the words in image are written in.
image is any ImageLike object.Returns a TesseractJob whose then, progress, error and finally methods can be used to act on the result of the script.
Tesseract.detect(myImage)
.then(function(result){
console.log(result)
})
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:
img, video, or canvas elementcanvas.getContext('2d'))File object (from a file <input> or drag-drop event)Blob objectImageData instance (an object containing width, height and data properties)In NodeJS, an image can be
Buffer instance containing a PNG or JPEG imageImageData instance (an object containing width, height and data properties)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. It also provides finally method, which will be fired regardless of the job fate. One important difference is that these methods return the job itself (to enable chaining) rather than new.
Typical use is:
Tesseract.recognize(myImage)
.progress(message => console.log(message))
.catch(err => console.error(err))
.then(result => console.log(result))
.finally(resultOrError => console.log(resultOrError))
Which is equivalent to:
var job1 = Tesseract.recognize(myImage);
job1.progress(message => console.log(message));
job1.catch(err => console.error(err));
job1.then(result => console.log(result));
job1.finally(resultOrError => console.log(resultOrError));
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}
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:
result 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]
}
Sets callback as the function that will be called if the job fails.
callback is a function with the signature callback(error) where error is a json object.Sets callback as the function that will be called regardless if the job fails or success.
callback is a function with the signature callback(resultOrError) where resultOrError is a json object.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',
})
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.
A string specifying the location of the tesseract.worker.js file. Set this string before calling Tesseract.recognize and Tesseract.detect if you want Tesseract.js to use a different file.
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.
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.
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
Thanks :)
FAQs
Pure Javascript Multilingual OCR
We found that tesseract.js demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 4 open source maintainers collaborating on the project.
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