MoodAnalyzer

MoodAnalyzer is a reusable function that uses TensorFlow.js and MobileNet to analyze the mood from an image.

Installation

You can install the package using npm:

npm install mood-analyzer

## Usage
Here’s an example of how to use the MoodAnalyzer function in your React Native project:

import React, { useState } from 'react';
import { View, Button, Image, Text } from 'react-native';
import * as ImagePicker from 'react-native-image-picker';
import MoodAnalyzer from 'mood-analyzer';

const App = () => {
  const [imageUri, setImageUri] = useState<string | null>(null);
  const [mood, setMood] = useState<string | null>(null);

  const pickImage = async () => {
    const result = await ImagePicker.launchImageLibrary({
      mediaType: 'photo',
      includeBase64: true,
    });

    if (result.assets && result.assets.length > 0) {
      const uri = result.assets[0].uri;
      if (uri) {
        setImageUri(uri);
        const moodResult = await MoodAnalyzer(result.assets[0].base64);
        setMood(moodResult);
      }
    }
  };

  return (
    <View>
      <Button title="Pick an Image" onPress={pickImage} />
      {imageUri && <Image source={{ uri: imageUri }} style={{ width: 200, height: 200 }} />}
      {mood && <Text>Mood: {mood}</Text>}
    </View>
  );
};

export default App;


## Function
MoodAnalyzer(base64: string | undefined): Promise<string | undefined>
Analyzes the mood from a base64-encoded image string and returns a mood prediction.

## Parameters
base64: A base64-encoded string of the image to analyze.

## Returns
A promise that resolves to a string indicating the mood (“Happy” or “Sad”) or an error message if the analysis fails.

## Dependencies
@tensorflow/tfjs: ^3.9.0
@tensorflow/tfjs-react-native: ^0.5.0
@tensorflow-models/mobilenet: ^2.1.0
canvas: ^2.8.0
react-native-image-picker: ^4.0.6

## License
This project is licensed under the MIT License - see the LICENSE file for details.