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MiniProject, a Flutter-based machine learning internship project, uses PoseNet for real-time posture detection. Employing the `tflite_flutter` package, it delivers instant feedback on user posture. Streamlined dependencies like `camera` and `image` enhance the app's efficiency in assessing and improving posture.

Kotlin 1.95% Batchfile 14.24% Dart 83.81%
flutter posenet-model tensorflow-lite tflite-models

irisintershipproject's Introduction

Internship Project

Description

This Flutter project is a machine learning internship project designed for posture detection using the PoseNet model. The application leverages the tflite_flutter package for efficient processing of the machine learning model.

Project Details

  • Name: MiniProject
  • Description: This is a machine learning internship project focused on real-time posture detection.
  • Version: 1.0.0+1
  • Flutter SDK: >=3.2.6 <4.0.0

Dependencies

The project relies on the following dependencies:

  • Flutter: Flutter
  • tflite_flutter: tflite_flutter
  • image: image
  • camera: camera

Getting Started

  1. Clone the repository: git clone https://github.com/adarshsavalagi/IrisInternshipProject.git
  2. Navigate to the project directory: cd MiniProject
  3. Run the app: flutter run

Usage

  1. Launch the application on your Flutter-compatible device.
  2. The app will start real-time posture detection using the PoseNet model.
  3. Receive feedback on your posture based on the model's predictions.

Feel free to contribute and enhance the project further!

Note

This project is part of a machine learning internship and is not intended for public release.

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