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This project provides a comprehensive, evidence-based platform supporting pregnant women with technology and expert guidance. Features include personalized exercise routines, custom nutrition plans, and essential guidelines. It uses React.js for frontend, Node.js, Express, Flask for backend, TensorFlow for ML, and OpenCV for posture analysis.

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Pregnancy Assistance Platform

Welcome to the Pregnancy Assistance Platform — a comprehensive solution designed to support pregnant women throughout their journey. This platform offers tailored diet plans based on health reports, provides accurate trimester-based guidance, and leverages machine learning to help women perform yoga with real-time posture analysis using OpenCV.

Table of Contents

Features

  1. Diet Recommendations:

    • Women can upload health reports, and the platform generates personalized diet plans based on these reports using a trained model.
  2. Trimester Guidance:

    • The platform offers trimester-specific information, including Do’s and Don’ts, to help women navigate each stage of pregnancy smoothly.
  3. Yoga Posture Analysis:

    • Leveraging machine learning and OpenCV, the platform allows pregnant women to practice yoga in front of a camera. The ML model analyzes and provides real-time feedback on their posture, ensuring they perform yoga poses correctly and safely.

Tech Stack

  • Frontend: Next.js
  • Backend: Node.js, Express.js
  • Database: MongoDB
  • Machine Learning: Python with OpenCV for yoga posture analysis
  • ML Libraries: Mediapipe, TensorFlow (if applicable)
  • Authentication: JSON Web Tokens (JWT)

Installation

Prerequisites

Make sure you have the following installed on your system:

Clone the Repository

frontend code

  • cd frontend
  • npm install
  • npm run dev

python models

  • cd models
  • install all the modules prompted in the terminal while running these python files using pip or pip3
  • python diet.py
  • python pose.py

About

This project provides a comprehensive, evidence-based platform supporting pregnant women with technology and expert guidance. Features include personalized exercise routines, custom nutrition plans, and essential guidelines. It uses React.js for frontend, Node.js, Express, Flask for backend, TensorFlow for ML, and OpenCV for posture analysis.

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  • Python 90.3%
  • C++ 6.5%
  • Cython 2.4%
  • C 0.7%
  • JavaScript 0.1%
  • Fortran 0.0%