ABSTRACT
- •The increasing need for health awareness and lifestyle management has increased demand for advanced dietary tracking solutions.
- • This project, titled “Food Recognition with Calorie Measurement and Personalized Diet Recommendation with Tracking System,” presents an innovative AI-driven system designed to assist users in achieving personalized health and fitness goals.
- • The system integrates food recognition through image processing and machine learning algorithms to automatically identify food items and provide precise calorie counts.
- •Using deep learning techniques, the platform can assess dietary intake and recommend customized meal plans tailored to individual dietary preferences, health conditions, and fitness objectives.
- •By incorporating a tracking system, the project enables users to monitor their daily intake, track nutritional progress, and adjust goals based on real-time data insights.
EXISTING SYSTEM
- •In current food recognition and diet-tracking systems, various applications and platforms allow users to track calorie intake and receive nutritional recommendations.
- •However, these systems often require extensive manual input, such as searching for food items in a database or manually entering quantities and serving sizes.
- •This approach can be time-consuming, especially for complex meals with multiple ingredients, and may lead to inaccuracies in calorie and nutrient tracking.
- •Some advanced existing systems use barcode scanning to retrieve nutritional information, which is helpful for packaged foods but ineffective for fresh or homemade meals.
DISADVANTAGES
- Barcode-Based Limitation:
- Systems that rely on barcode scanning work well for packaged foods but fail to capture nutritional data for homemade meals, fresh produce, or restaurant dishes.
- Limited Accuracy with Complex Dishes:
- Image recognition technology in current systems often struggles with mixed dishes or complex meals, resulting in inaccurate food identification and calorie estimates.
- Lack of Personalized Diet Recommendations:
- Most existing systems offer general dietary advice, lacking the personalization needed to meet specific health goals, dietary preferences, or restrictions, which limits their effectiveness for individualized health management.
- Inconsistent Portion Size Estimation:
- Existing systems often have difficulty accurately estimating portion sizes from images, which can lead to incorrect calorie and nutrient calculations.
PROPOSED SYSTEM
- •The proposed system leverages YOLO v8 (You Only Look Once), a state-of-the-art object detection algorithm, to create an advanced food recognition and calorie tracking solution. YOLO v8’s speed and accuracy make it an ideal choice for real-time food identification, capable of detecting multiple items in a single image with high precision. By integrating YOLO v8 with calorie databases and personalized diet recommendation models, the system provides a seamless, efficient, and user-friendly experience for dietary tracking.
- •Real-Time Food Recognition with YOLO v8:
- •YOLO v8’s advanced object detection capabilities allow the system to identify various food items quickly and accurately in real-time, even in complex and mixed dishes.
- •The system is trained on an extensive food dataset covering a wide range of cuisines and ingredients, ensuring high accuracy in recognizing diverse food types and portions.
- •Calorie and Nutritional Estimation:
- •Once foods are identified, the system accesses a nutrition database to provide accurate calorie counts, along with macronutrient (carbohydrates, proteins, fats) and micronutrient (vitamins, minerals) breakdowns.
- •YOLO v8’s bounding box predictions enable more accurate portion size estimation, improving calorie and nutrient calculations for each food item.
- •Personalized Diet Recommendations:
- •The system uses AI to offer diet recommendations tailored to individual health goals, dietary restrictions, and preferences, making it suitable for users with specific health conditions (e.g., diabetes, high blood pressure) or fitness objectives (e.g., weight loss, muscle gain).
- •Meal suggestions are provided based on daily dietary intake, helping users balance their nutrition in real-time.
- •Progress Tracking and Goal Setting:
- •The system tracks daily, weekly, and monthly dietary intake and nutritional balance, enabling users to monitor their progress over time.
- •Goal-setting options allow users to customize targets, such as daily calorie intake or macronutrient distribution, and the system adjusts recommendations to help users stay on track.
- •
ADVANTAGES
- Lightweight and Efficient:
- YOLO is designed for real-time object detection, making it suitable for instantly recognizing food items as soon as an image is captured or uploaded. This can provide users with immediate feedback on their calorie intake, enhancing the responsiveness of the system.
- High Performance with Low Latency:
- YOLO is capable of detecting multiple objects within an image and drawing bounding boxes around them. This is useful for food recognition, as users may have multiple food items in one image (e.g., a meal with various ingredients or dishes). YOLO can identify and label each item individually, enabling accurate calorie measurements for each recognized food.
- YOLO’s efficiency allows it to run on devices with limited computational resources, such as smartphones. This is an advantage if you plan to deploy the application on mobile platforms where users can directly capture and analyze food images.
PROJECT DEMO VIDEO
HARDWARE REQUIREMENTS:
- System : Intel i3 Processor Mimimum.
- Hard Disk : 20 GB Space
- Monitor : 15’’ LED
- Input Devices : Keyboard, Mouse
- Ram : 4 GB
SOFTWARE REQUIREMENTS:
- •Operating system : Windows 10 Pro. /Mac Os
- •Coding Language : Python, HTML, CSS,JS
- •Web Framework : Flask
Including Packages
=======================
- * Base Paper
- * Complete Source Code
- * Complete Documentation
- * Complete Presentation Slides
- * Flow Diagram
- * Database File
- * Screenshots
- * Execution Procedure
- * Readme File
- * Addons
- * Video Tutorials
- * Supporting Softwares
Specialization =======================
- * Voice Conference
- * Video On Demand
- * Remote Connectivity
- * Code Customization
- * Document Customization
- * Live Chat Support