PANTS is a self-hosted, open-source nutrition tracker and tool for nutritional data analysis of ingredients and recipes.

Manage your meals, your calories and your biometric data. It has it's own products and additives database

Find and save high protein recipes quickly!

Бот для телеграмма для отслеживания потребления еды и тренировок

Yandex Lyceum Telegram bot project

Scripts for interacting with calories, to fuzzy select new entries to add, swap/merge databases

Web application that helps users track the food they eat, along with information such as ingredients and caloric intake.

Calories Tracker (Camera + AI)

Helps you effortlessly track your daily meals and provide insights

Calorie counter and tracker built in Django.

Calories Counter Django Application

A Python application that uses external APIs to retrieve nutritional data, compute BMI/BMR, and generate personalized dietary recommendations

Novel Hybrid Embedding Color-Texture Network

NutriFy is a full-stack web application that uses Artificial Intelligence to recognize Indian food items from images and estimate their calorie and nutritional information. The application combines YOLOv8n instance segmentation model with a Flask backend and an interactive frontend to help users make healthier food choices.

Desktop nutrition and calorie tracking application written in Python using CustomTkinter and SQLite.

Streamlit app using Google Gemini AI to analyze food images, identify items, and estimate calories — fast, accurate, and browser-based.

This is a food tracking project that gets the calorie related information from the Open-Source Llama model, stores it in your database incase if you want to add them as the food consumed, provides step by step instructions to prepare the dish and also allows you to chat with it so that you can ask your queries.

Calorie Counting program using Python that can have the user add new users, their weights by today's date and their calorie intake each day (2021).

Machine Learning-powered REST API for predicting calories burned during exercise using XGBoost. Built with Flask and Docker, providing fast and accurate calorie predictions through a simple API.

Personal nutrition assistant with Telegram and mobile web interfaces, OpenAI text/image flows, shared SQLite history, localization, Docker, and tests.