Pure Javascript OCR for more than 100 Languages 📖🎉🖥
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API


createWorker(options): Worker

createWorker is a factory function that creates a tesseract worker, a worker is basically a Web Worker in browser and Child Process in Node.

Arguments:

  • options an object of customized options
    • corePath path for tesseract-core.js script
    • langPath path for downloading traineddata, do not include / at the end of the path
    • workerPath path for downloading worker script
    • dataPath path for saving traineddata in WebAssembly file system, not common to modify
    • cachePath path for the cached traineddata, more useful for Node, for browser it only changes the key in IndexDB
    • cacheMethod a string to indicate the method of cache management, should be one of the following options
      • write: read cache and write back (default method)
      • readOnly: read cache and not to write back
      • refresh: not to read cache and write back
      • none: not to read cache and not to write back
    • workerBlobURL a boolean to define whether to use Blob URL for worker script, default: true
    • gzip a boolean to define whether the traineddata from the remote is gzipped, default: true
    • logger a function to log the progress, a quick example is m => console.log(m)
    • errorHandler a function to handle worker errors, a quick example is err => console.error(err)

Examples:

const { createWorker } = Tesseract;
const worker = await createWorker({
  langPath: '...',
  logger: m => console.log(m),
});

Worker

A Worker helps you to do the OCR related tasks, it takes few steps to setup Worker before it is fully functional. The full flow is:

  • FS functions // optional
  • loadLanguauge
  • initialize
  • setParameters // optional
  • recognize or detect
  • terminate

Each function is async, so using async/await or Promise is required. When it is resolved, you get an object:

{
  "jobId": "Job-1-123",
  "data": { ... }
}

jobId is generated by Tesseract.js, but you can put your own when calling any of the function above.

Worker.writeText(path, text, jobId): Promise

Worker.writeText() writes a text file to the path specified in MEMFS, it is useful when you want to use some features that requires tesseract.js to read file from file system.

Arguments:

  • path text file path
  • text content of the text file
  • jobId Please see details above

Examples:

(async () => {
  await worker.writeText('tmp.txt', 'Hi\nTesseract.js\n');
})();

Worker.readText(path, jobId): Promise

Worker.readText() reads a text file to the path specified in MEMFS, it is useful when you want to check the content.

Arguments:

  • path text file path
  • jobId Please see details above

Examples:

(async () => {
  const { data } = await worker.readText('tmp.txt');
  console.log(data);
})();

Worker.removeFile(path, jobId): Promise

Worker.readFile() remove a file in MEMFS, it is useful when you want to free the memory.

Arguments:

  • path file path
  • jobId Please see details above

Examples:

(async () => {
  await worker.removeFile('tmp.txt');
})();

Worker.FS(method, args, jobId): Promise

Worker.FS() is a generic FS function to do anything you want, you can check HERE for all functions.

Arguments:

  • method method name
  • args array of arguments to pass
  • jobId Please see details above

Examples:

(async () => {
  await worker.FS('writeFile', ['tmp.txt', 'Hi\nTesseract.js\n']);
  // equal to:
  // await worker.readText('tmp.txt', 'Hi\nTesseract.js\n');
})();

Worker.loadLanguage(langs, jobId): Promise

Worker.loadLanguage() loads traineddata from cache or download traineddata from remote, and put traineddata into the WebAssembly file system.

Arguments:

  • langs a string to indicate the languages traineddata to download, multiple languages are concated with +, ex: eng+chi_tra
  • jobId Please see details above

Examples:

(async () => {
  await worker.loadLanguage('eng+chi_tra');
})();

Worker.initialize(langs, oem, jobId): Promise

Worker.initialize() initializes the Tesseract API, make sure it is ready for doing OCR tasks.

Arguments:

  • langs a string to indicate the languages loaded by Tesseract API, it can be the subset of the languauge traineddata you loaded from Worker.loadLanguage.
  • oem a enum to indicate the OCR Engine Mode you use
  • jobId Please see details above

Examples:

(async () => {
  /** You can load more languages in advance, but use only part of them in Worker.initialize() */
  await worker.loadLanguage('eng+chi_tra');
  await worker.initialize('eng');
})();

Worker.setParameters(params, jobId): Promise

Worker.setParameters() set parameters for Tesseract API (using SetVariable()), it changes the behavior of Tesseract and some parameters like tessedit_char_whitelist is very useful.

Arguments:

  • params an object with key and value of the parameters
  • jobId Please see details above

Useful Paramters:

name type default value description
tessedit_ocr_engine_mode enum OEM.DEFAULT Check HERE for definition of each mode
tessedit_pageseg_mode enum PSM.SINGLE_BLOCK Check HERE for definition of each mode
tessedit_char_whitelist string '' setting white list characters makes the result only contains these characters, useful the content in image is limited
preserve_interword_spaces string '0' '0' or '1', keeps the space between words
user_defined_dpi string '' Define custom dpi, use to fix Warning: Invalid resolution 0 dpi. Using 70 instead.

This list is incomplete. As Tesseract.js passes parameters to the Tesseract engine, all parameters supported by the underlying version of Tesseract should also be supported by Tesseract.js. (Note that parameters marked as “init only” in Tesseract documentation cannot be set by setParameters or recognize.)

Examples:

(async () => {
  await worker.setParameters({
    tessedit_char_whitelist: '0123456789',
  });
})

Worker.recognize(image, options, jobId): Promise

Worker.recognize() provides core function of Tesseract.js as it executes OCR

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

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

Arguments:

  • image see Image Format for more details.
  • options an object of customized options
    • rectangle an object to specify the regions you want to recognized in the image, should contain top, left, width and height, see example below.
  • output an object specifying which output formats to return (by default text, blocks, hocr, and tsv are returned)
  • jobId Please see details above

Output:

Examples:

const { createWorker } = Tesseract;
(async () => {
  const worker = await createWorker();
  await worker.loadLanguage('eng');
  await worker.initialize('eng');
  const { data: { text } } = await worker.recognize(image);
  console.log(text);
})();

With rectangle

const { createWorker } = Tesseract;
(async () => {
  const worker = await createWorker();
  await worker.loadLanguage('eng');
  await worker.initialize('eng');
  const { data: { text } } = await worker.recognize(image, {
    rectangle: { top: 0, left: 0, width: 100, height: 100 },
  });
  console.log(text);
})();

Worker.detect(image, jobId): Promise

Worker.detect() does OSD (Orientation and Script Detection) to the image instead of OCR.

Arguments:

  • image see Image Format for more details.
  • jobId Please see details above

Examples:

const { createWorker } = Tesseract;
(async () => {
  const worker = await createWorker();
  await worker.loadLanguage('eng');
  await worker.initialize('eng');
  const { data } = await worker.detect(image);
  console.log(data);
})();

Worker.terminate(jobId): Promise

Worker.terminate() terminates the worker and cleans up

(async () => {
  await worker.terminate();
})();

createScheduler(): Scheduler

createScheduler() is a factory function to create a scheduler, a scheduler manages a job queue and workers to enable multiple workers to work together, it is useful when you want to speed up your performance.

Examples:

const { createScheduler } = Tesseract;
const scheduler = createScheduler();

Scheduler

Scheduler.addWorker(worker): string

Scheduler.addWorker() adds a worker into the worker pool inside scheduler, it is suggested to add one worker to only one scheduler.

Arguments:

  • worker see Worker above

Examples:

const { createWorker, createScheduler } = Tesseract;
const scheduler = createScheduler();
const worker = await createWorker();
scheduler.addWorker(worker);

Scheduler.addJob(action, ...payload): Promise

Scheduler.addJob() adds a job to the job queue and scheduler waits and finds an idle worker to take the job.

Arguments:

  • action a string to indicate the action you want to do, right now only recognize and detect are supported
  • payload a arbitrary number of args depending on the action you called.

Examples:

(async () => {
 const { data: { text } } = await scheduler.addJob('recognize', image, options);
 const { data } = await scheduler.addJob('detect', image);
})();

Scheduler.getQueueLen(): number

Scheduler.getNumWorkers() returns the length of job queue.

Scheduler.getNumWorkers(): number

Scheduler.getNumWorkers() returns number of workers added into the scheduler

Scheduler.terminate(): Promise

Scheduler.terminate() terminates all workers added, useful to do quick clean up.

Examples:

(async () => {
  await scheduler.terminate();
})();

setLogging(logging: boolean)

setLogging() sets the logging flag, you can setLogging(true) to see detailed information, useful for debugging.

Arguments:

  • logging boolean to define whether to see detailed logs, default: false

Examples:

const { setLogging } = Tesseract;
setLogging(true);

recognize(image, langs, options): Promise

recognize() is a function to quickly do recognize() task, it is not recommended to use in real application, but useful when you want to save some time.

See Tesseract.js

detect(image, options): Promise

Same background as recognize(), but it does detect instead.

See Tesseract.js

PSM

See PSM.js

OEM

See OEM.js