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    235
  • Rank 170,480 (Top 4 %)
  • Language
    Java
  • License
    MIT License
  • Created over 2 years ago
  • Updated 6 months ago

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Repository Details

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

vision-camera-ocr

A VisionCamera 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-reanimated/plugin',
      {
        globals: ['__scanOCR'],
      },
    ],

    // ...

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

Usage

import { labelImage } from "vision-camera-image-labeler";

// ...
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