@chuvincent/vision-camera-mlkit
v2.6.1
Published
VisionCamera Frame Processor Plugin to provide general bridge to MLKit. Based on ismaelmoreiraa's fixes for OCR
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vision-camera-mlkit
Supports general bridge between Vision Camera and Google ML Kit
Installation
npm install @chuvincent/vision-camera-mlkit
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 '@chuvincent/vision-camera-mlkit';
// ...
const frameProcessor = useFrameProcessor((frame) => {
'worklet';
const scannedOcr = scanOCR(frame);
}, []);
Publish to NPM
npm run prepare
npm run release
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