VerticalOCRModule

TypeScript API implementation of the useVerticalOCR hook.

Reference

import {
  VerticalOCRModule,
  VERTICAL_OCR_ENGLISH,
} from 'react-native-executorch';

const imageUri = 'path/to/image.png';

// Creating an instance
const verticalOCRModule = new VerticalOCRModule();

// Loading the model
await verticalOCRModule.load(VERTICAL_OCR_ENGLISH);

// Running the model
const detections = await verticalOCRModule.forward(imageUri);

Methods

Method	Type	Description
load	(model: { detectorLarge: ResourceSource; detectorNarrow: ResourceSource; recognizerLarge: ResourceSource; recognizerSmall: ResourceSource; language: OCRLanguage }, independentCharacters: boolean, onDownloadProgressCallback?: (progress: number) => void): Promise<void>	Loads the model, where detectorLarge is a string that specifies the location of the recognizer binary file which accepts input images with a width of 1280 pixels, detectorNarrow is a string that specifies the location of the detector binary file which accepts input images with a width of 320 pixels, recognizerLarge is a string that specifies the location of the recognizer binary file which accepts input images with a width of 512 pixels, recognizerSmall is a string that specifies the location of the recognizer binary file which accepts input images with a width of 64 pixels, and language is a parameter that specifies the language of the text to be recognized by the OCR.
forward	(input: string): Promise<OCRDetections[]>	Executes the model's forward pass, where input can be a fetchable resource or a Base64-encoded string.
delete	(): void	Release the memory held by the module. Calling forward afterwards is invalid. Note that you cannot delete model while it's generating.

Type definitions

interface DetectorSources {
  detectorLarge: string | number;
  detectorNarrow: string | number;
}

interface RecognizerSources {
  recognizerLarge: string | number;
  recognizerSmall: string | number;
}

type OCRLanguage =
  | 'abq'
  | 'ady'
  | 'af'
  | 'ava'
  | 'az'
  | 'be'
  | 'bg'
  | 'bs'
  | 'chSim'
  | 'che'
  | 'cs'
  | 'cy'
  | 'da'
  | 'dar'
  | 'de'
  | 'en'
  | 'es'
  | 'et'
  | 'fr'
  | 'ga'
  | 'hr'
  | 'hu'
  | 'id'
  | 'inh'
  | 'ic'
  | 'it'
  | 'ja'
  | 'kbd'
  | 'kn'
  | 'ko'
  | 'ku'
  | 'la'
  | 'lbe'
  | 'lez'
  | 'lt'
  | 'lv'
  | 'mi'
  | 'mn'
  | 'ms'
  | 'mt'
  | 'nl'
  | 'no'
  | 'oc'
  | 'pi'
  | 'pl'
  | 'pt'
  | 'ro'
  | 'ru'
  | 'rsCyrillic'
  | 'rsLatin'
  | 'sk'
  | 'sl'
  | 'sq'
  | 'sv'
  | 'sw'
  | 'tab'
  | 'te'
  | 'th'
  | 'tjk'
  | 'tl'
  | 'tr'
  | 'uk'
  | 'uz'
  | 'vi';

interface Point {
  x: number;
  y: number;
}

interface OCRDetection {
  bbox: Point[];
  text: string;
  score: number;
}

Loading the model

To load the model, use the load method. It accepts:

model - Object containing the detector sources, recognizer sources, and language.

• detectorLarge - A string that specifies the location of the recognizer binary file which accepts input images with a width of 1280 pixels.
• detectorNarrow - A string that specifies the location of the detector binary file which accepts input images with a width of 320 pixels.
• recognizerLarge - A string that specifies the location of the recognizer binary file which accepts input images with a width of 512 pixels.
• recognizerSmall - A string that specifies the location of the recognizer binary file which accepts input images with a width of 64 pixels.
• language - A parameter that specifies the language of the text to be recognized by the OCR.

independentCharacters – A boolean parameter that indicates whether the text in the image consists of a random sequence of characters. If set to true, the algorithm will scan each character individually instead of reading them as continuous text.

onDownloadProgressCallback - (Optional) Function called on download progress.

This method returns a promise, which can resolve to an error or void.

For more information on loading resources, take a look at loading models page.

Running the model

To run the model, you can use the forward method. It accepts one argument, which is the image. The image can be a remote URL, a local file URI, or a base64-encoded image. The method returns a promise, which can resolve either to an error or an array of OCRDetection objects. Each object contains coordinates of the bounding box, the label of the detected object, and the confidence score.