new with online tf model

import React, { useEffect, useRef } from 'react';

import { View, StyleSheet, Dimensions, Image } from 'react-native';

import VLCPlayer from 'react-native-vlc-player';

import * as tf from '@tensorflow/tfjs';

import { fetch } from '@tensorflow/tfjs-react-native';


const ObjectDetection = () => {

  const vlcPlayerRef = useRef(null);

  const modelRef = useRef(null);

  const streamingRef = useRef(false);


  useEffect(() => {

    const loadModel = async () => {

      try {

        await tf.ready();

        modelRef.current = await tf.loadGraphModel(

          fetch(

            'https://tfhub.dev/tensorflow/ssd_mobilenet_v2/2/default/1',

            { method: 'GET' }

          )

        );

        streamingRef.current = true;

      } catch (error) {

        console.error('Error loading model:', error);

      }

    };


    loadModel();

  }, []);


  const processFrame = async () => {

    if (!streamingRef.current) {

      return;

    }


    try {

      const snapshot = await vlcPlayerRef.current.takeSnapshot(true);

      const imageTensor = await tf.image.load(`data:image/jpeg;base64,${snapshot}`);

      const preprocessedTensor = imageTensor.resizeBilinear([300, 300]).expandDims();

      const predictions = await modelRef.current.executeAsync(preprocessedTensor);


      // Process the predictions and perform necessary actions

      processPredictions(predictions);


      imageTensor.dispose();

      preprocessedTensor.dispose();

      tf.dispose(predictions);

    } catch (error) {

      console.error('Error processing frame:', error);

    }


    requestAnimationFrame(processFrame);

  };


  const processPredictions = (predictions) => {

    // Process the predictions and perform necessary actions

    // You can iterate over the predictions and extract relevant information

    // For example, you can filter predictions based on a certain threshold,

    // draw bounding boxes on the image, or trigger other events based on detected objects.


    // Here's an example of logging the top prediction:

    const topPrediction = predictions[0].dataSync();

    console.log('Top prediction:', topPrediction);

  };


  useEffect(() => {

    processFrame();


    return () => {

      streamingRef.current = false;

    };

  }, []);


  return (

    <View style={styles.container}>

      <VLCPlayer

        ref={vlcPlayerRef}

        style={styles.videoPlayer}

        videoAspectRatio="16:9"

        source={{

          uri: 'rtsp://admin:admin@192.168.184.64:1935',

          autoplay: true,

          initOptions: ['--rtsp-tcp'],

        }}

      />

      {/* Add any UI components or overlays as needed */}

      {/* Example: Display the processed frame */}

      <View style={styles.overlay}>

        <Image style={styles.processedImage} />

      </View>

    </View>

  );

};


const styles = StyleSheet.create({

  container: {

    flex: 1,

  },

  videoPlayer: {

    flex: 1,

    width: Dimensions.get('window').width,

    height: Dimensions.get('window').height,

  },

  overlay: {

    position: 'absolute',

    top: 0,

    left: 0,

    width: Dimensions.get('window').width,

    height: Dimensions.get('window').height,

    justifyContent: 'center',

    alignItems: 'center',

  },

  processedImage: {

    width: Dimensions.get('window').width,

    height: Dimensions.get('window').height,

    resizeMode: 'cover',

  },

});


export default ObjectDetection;


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