Advanced Personalized Diet Planner

The Advanced Personalized Diet Planner is a professional-grade software designed to help users generate customized meal plans based on their daily calorie targets. This version includes advanced features such as visual analytics, the ability to import custom datasets, and AI-powered meal recommendations using machine learning.

Features

Interactive GUI:

• User-friendly interface built with Tkinter.
• Seamlessly guides users through calorie-based meal planning.

Visual Analytics:

• Generates dynamic graphs to visualize calorie distribution in the dataset.
• Interactive bar charts for better decision-making.

Custom Dataset Import:

• Allows users to upload their own meal datasets via a file dialog.
• Supports CSV file format.

AI-Powered Meal Recommendations:

• Uses scikit-learn (K-Nearest Neighbors) to recommend meals based on calorie targets.
• Recommends the closest matching meals for effective planning.

Preloaded Sample Dataset:

• Includes a dataset of 1000+ meals with calorie values.
• Easily extendable with imported datasets.

Error Handling:

• Ensures robustness by handling invalid inputs and corrupted datasets gracefully.

Target Audience

• Nutritionists and Dietitians: Use as a tool to plan meals for clients.
• Fitness Enthusiasts: Plan meals to meet dietary goals.
• Developers and Learners: Learn advanced Python concepts like GUI development and machine learning.

Tech Stack

1. Programming Language: Python
2. Libraries:

• Tkinter for GUI
• pandas for data processing
• matplotlib for visualization
• scikit-learn for machine learning (KNN model)

1. Dataset:

• Preloaded sample_meals.csv with 1000+ entries.

Installation and Usage Guide

Prerequisites

• Python 3.8 or higher
• Required libraries (pandas, matplotlib, scikit-learn)

Installation

1. cd advanced-diet-planner
2. Set up a virtual environment:
3. python -m venv .venv
4. source .venv/bin/activate # Windows: .venv\Scripts\activate
5. Install dependencies:
6. pip install -r requirements.txt

DietPlanner/

├── data/           

│  ├── sample_meals.csv   # Preloaded dataset with 1000+ meals and calorie values

├── gui/            

│  ├── __init__.py      # Makes the folder a Python package

│  ├── diet_gui.py      # GUI implementation

├── utils/           

│  ├── __init__.py      # Makes the folder a Python package

│  ├── diet_logic.py     # Backend logic for meal planning and ML recommendations

├── main.py          # Entry point for the application

├── generate_csv.py      # Script to generate the sample_meals.csv file

├── requirements.txt     # List of dependencies for the project

Usage

1. Run the application:
2. python main.py
3. Features:

• Input a calorie target and generate a meal plan.
• Upload a custom dataset via the "Import Dataset" button.
• View graphs and recommended meals.

Why Buy This Project?

Value Proposition

• Combines usability and advanced analytics for practical meal planning.
• Saves time for users with AI-powered meal recommendations.
• Offers a customizable experience through dataset imports.

Educational Value

• Ideal for students and developers to learn:
• Python-based GUI development (Tkinter).
• Data analysis and visualization (pandas, matplotlib).
• Machine learning implementation (scikit-learn).

Pre-Built Product:

• Ready-to-use, with clean code and proper documentation.
• Buyers can directly integrate this tool into their personal or professional use.

Educational Project:

• Suitable for portfolio building or as a learning project for Python and ML enthusiasts.

Author: Kartikeya Mishra