diva-mobile-vision-camera-ocr-plugin v0.0.5

vision-camera-ocr-plugin

A VisionCamera Frame Processor Plugin to preform text detection on images using MLKit Vision Text Recognition. This module can be used only with React Native Vision Camera >= v3.x.x

Installation

yarn add vision-camera-ocr-plugin
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 {OCRFrame, scanOCR} from 'vision-camera-ocr-plugin';
import {
  useFrameProcessor,
  Camera,
  useCameraDevice,
} from 'react-native-vision-camera';
import {Worklets} from 'react-native-worklets-core';

export default ({onTextClicked}: VisionCameraPlateProps) => {
  const [hasPermission, setHasPermission] = React.useState(false);
  const [ocr, setOcr] = React.useState<OCRFrame>();
  const isFocused = useIsFocused();
  const device = useCameraDevice('back');

  const onCodeDetected = Worklets.createRunInJsFn((data: any) => {
    setOcr(data);
  });

  const frameProcessor = useFrameProcessor(frame => {
    'worklet';
    const data = scanOCR(frame);
    onCodeDetected(data);
  }, []);

  React.useEffect(() => {
    (async () => {
      const status = await Camera.requestCameraPermission();
      setHasPermission(status === 'granted');
    })();
  }, []);


  return (
    <>
      {device !== undefined && hasPermission ? (
        <Camera
          frameProcessor={frameProcessor}
          device={device}
          isActive={isFocused}
          pixelFormat="yuv"
        />
      ) : (
        <View>
          <Text>No available cameras</Text>
        </View>
      )}
    </>
  );
};

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