TensorflowReactNative

This React Native app, powered by TensorFlow.js, offers real-time image classification. Users can capture photos using the device's camera or analyze objects in real-time, providing instant insights into object and scene identification through machine learning.

Project Structure

• App.js: This is the main entry point of the application. It sets up the navigation and the screens of the app.

• Components/: This directory contains the main components of the application:

  • BoundingBox.js: This component is responsible for rendering bounding boxes around detected objects in an image.
  • ImagePickerAndResizer.js: This component allows the user to pick an image from their device and resizes it for prediction or detection.
  • ObjectDetection.js: This component handles object detection in selected images.
  • Predictions.js: This component handles image prediction for selected images.

• assets/tfjs_model/: This directory contains the TensorFlow.js model (model.json) and the labels (labels.json) used for image prediction and object detection.

• package.json: This file lists the project dependencies and scripts.

Installation

To install the project, you need to have Node.js and npm installed. Then, you can clone the repository and install the dependencies:

git clone https://github.com/Alexis-Papazoglou/TensorflowReactNative.git
cd TensorflowReactNative
npm install

Running the Application

To start the application, run:

npm start

This will start the Metro Bundler and you can open the app in an emulator or on a physical device.

Features

• Image Prediction: This feature allows users to select an image and get predictions about what the image contains.

• Object Detection: This feature allows users to select an image and detect objects within the image. Detected objects are highlighted with bounding boxes.

Contributing

Contributions are welcome. Please open an issue to discuss your ideas or submit a pull request with your changes.