vvet_backend_1/node_modules/tesseract.js/docs/api.md

API

• createWorker()
  • Worker.recognize
  • Worker.setParameters
  • Worker.reinitialize
  • Worker.detect
  • Worker.terminate
  • Worker.writeText
  • Worker.readText
  • Worker.removeFile
  • Worker.FS
• createScheduler()
  • Scheduler.addWorker
  • Scheduler.addJob
  • Scheduler.getQueueLen
  • Scheduler.getNumWorkers
• setLogging()
• recognize()
• detect()
• PSM
• OEM

---

createWorker(options): Worker

createWorker is a function that creates a Tesseract.js worker. A Tesseract.js worker is an object that creates and manages an instance of Tesseract running in a web worker (browser) or worker thread (Node.js). Once created, OCR jobs are sent through the worker.

Arguments:

• langs a string to indicate the languages traineddata to download, multiple languages are specified using an array (['eng', 'chi_sim'])
• oem a enum to indicate the OCR Engine Mode you use
• options an object of customized options
  • corePath path to a directory containing both tesseract-core.wasm.js and tesseract-core-simd.wasm.js from Tesseract.js-core package
    • Setting corePath to a specific .js file is strongly discouraged. To provide the best performance on all devices, Tesseract.js needs to be able to pick between tesseract-core.wasm.js and tesseract-core-simd.wasm.js. See this issue for more detail.
  • 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
  • legacyCore set to true to ensure any code downloaded supports the Legacy model (in addition to LSTM model)
  • legacyLang set to true to ensure any language data downloaded supports the Legacy model (in addition to LSTM model)
  • 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)
• config an object of customized options which are set prior to initialization
  • This argument allows for setting "init only" Tesseract parameters
    • Most Tesseract parameters can be set after a worker is initialized, using either worker.setParameters or the options argument of worker.recognize.
    • A handful of Tesseract parameters, referred to as "init only" parameters in Tesseract documentation, cannot be modified after Tesseract is initialized--these can only be set using this argument
      • Examples include load_system_dawg, load_number_dawg, and load_punc_dawg

Examples:

const { createWorker } = Tesseract;
const worker = await createWorker('eng', 1, {
  langPath: '...',
  logger: m => console.log(m),
});

worker.recognize(image, options, output, 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.

[!TIP] 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 only text is returned)
  • Other options include blocks (json), hocr, and tsv
• jobId Please see details above

Output: worker.recognize returns a promise to an object containing jobId and data properties. The data property contains output in all of the formats specified using the output argument.

[!NOTE]
worker.recognize still returns an output object even if no text is detected (the outputs will simply contain no words). No exception is thrown as determining the page is empty is considered a valid result.

Examples:

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

With rectangle

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

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

Note: worker.setParameters cannot be used to change the oem, as this value is set at initialization. oem is initially set using an argument of createWorker. After a worker already exists, changing oem requires running worker.reinitialize.

Useful Parameters:

name	type	default value	description
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 if 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.reinitialize(langs, oem, jobId): Promise

worker.reinitialize() re-initializes an existing Tesseract.js worker with different langs and oem arguments.

Arguments:

• langs a string to indicate the languages traineddata to download, multiple languages are specified using an array (['eng', 'chi_sim'])
• oem a enum to indicate the OCR Engine Mode you use
• config an object of customized options which are set prior to initialization (see details above)
• jobId Please see details above

Note: to switch from Tesseract LSTM (oem value 1) to Tesseract Legacy (oem value 0) using worker.reinitialize(), the worker must already contain the code required to run the Tesseract Legacy model. Setting legacyCore: true and legacyLang: true in createWorker options ensures this is the case.

Examples:

await worker.reinitialize('eng', 1);

worker.detect(image, jobId): Promise

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

[!NOTE]
Running worker.detect requires a worker with code and language data that supports Tesseract Legacy (this is not enabled by default). If you want to run worker.detect, set legacyCore and legacyLang to true in the createWorker options.

Arguments:

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

Examples:

const { createWorker } = Tesseract;
(async () => {
  const worker = await createWorker('eng', 1, {legacyCore: true, legacyLang: true});
  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();
})();

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.removeFile removes 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.writeText('tmp.txt', 'Hi\nTesseract.js\n');
})();

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.getQueueLen() 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

[!WARNING]
This function is depreciated and should be replaced with worker.recognize (see above).

recognize works the same as worker.recognize, except that a new worker is created, loaded, and destroyed every time the function is called.

See Tesseract.js

detect(image, options): Promise

[!WARNING]
This function is depreciated and should be replaced with worker.detect (see above).

detect works the same as worker.detect, except that a new worker is created, loaded, and destroyed every time the function is called.

See Tesseract.js

PSM

See PSM.js

OEM

See OEM.js