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VisionCamera Frame Processor Plugin to detect text in real time using MLKit Text Detector (OCR)

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vision-camera-ocr

A VisionCamera v4 Frame Processor Plugin to preform text detection on images using MLKit Vision Text Recognition.

Installation

yarn add vision-camera-ocr
cd ios && pod install

Add the plugin to your babel.config.js:

module.exports = {
   plugins: [['react-native-worklets-core/plugin']],
    // ...

Note: You have to restart metro-bundler for changes in the babel.config.js file to take effect.

Usage

import {scanOCR} from 'vision-camera-ocr';

// ...
const frameProcessor = useFrameProcessor((frame) => {
  'worklet';
  const scannedOcr = scanOCR(frame);
}, []);

Data

scanOCR(frame) returns an OCRFrame with the following data shape. See the example for how to use this in your app.

 OCRFrame = {
   result: {
     text: string, // Raw result text
     blocks: Block[], // Each recognized element broken into blocks
   ;
};

The text object closely resembles the object documented in the MLKit documents. https://developers.google.com/ml-kit/vision/text-recognition#text_structure

The Text Recognizer segments text into blocks, lines, and elements. Roughly speaking:

a Block is a contiguous set of text lines, such as a paragraph or column,

a Line is a contiguous set of words on the same axis, and

an Element is a contiguous set of alphanumeric characters ("word") on the same axis in most Latin languages, or a character in others

Contributing

See the contributing guide to learn how to contribute to the repository and the development workflow.

License

MIT

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VisionCamera Frame Processor Plugin to detect text in real time using MLKit Text Detector (OCR)

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