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Ananda Technologies Pvt. Ltd.
  • AI & ML
  • Java
  • Android
  • 33% OFF

Food Calorie Estimation from Image

NutriSnap is an Android app in Java that recognises common Indian dishes from a meal photo using an on-device TFLite model, estimates calories, protein, carbs and fat, and tracks daily intake against a personal target. It includes a dietitian role for advice, a PHP admin panel with MySQL, a full project report and a setup guide.

ForDiplomaMCAB.Tech· CSE, IT

Platform
Android + Web API
1-on-1 setup
AnyDesk / Meet
Setup time
2 Hour
Download access
8 months
  • Source code
  • Project report
  • Setup guide

About this project

About the project

NutriSnap – Food Calorie Estimation from Image is a complete Android academic project. The user takes a photo of a meal, the app recognises the dish among 25 common Indian dishes using a TensorFlow Lite image classifier, and shows the calories and nutrients for the chosen portion. Meals are saved to a daily diary and compared with a personal calorie target worked out from height, weight, age and activity level.

How it works

  1. The user signs up and sets a goal (lose, maintain or gain weight). The app works out BMI, daily calories and macros using the Mifflin–St Jeor formula.
  2. The user snaps or picks a meal photo. The TFLite model runs on the phone and shows the top dish with a confidence score and two alternatives.
  3. The user confirms the dish and portion size. Calories, protein, carbs and fat are saved to the diary.
  4. Home, diary and progress screens show today's intake vs target, weekly charts, a weight trend and water glasses.
  5. A dietitian reviews the client's meals and writes advice. The admin manages foods, users, quiz, badges and reports from the web panel.

Users

  • User – scans meals, adds food manually, sets goals, sees charts, takes the nutrition quiz, earns badges and chooses a dietitian.
  • Dietitian – accepts client requests, sees client meals and progress, writes advice.
  • Admin – manages users, dietitian approval, food categories, the food database (40 dishes), meals, quiz, badges, notices, reports and settings.

Highlights

  • On-device TFLite CNN (MobileNetV2 transfer learning) – no internet needed for detection
  • Colour-match fallback with a clear "please confirm" step when the model is not sure
  • Personal calorie and macro target using a real nutrition formula
  • Streak, points and badges to keep users logging
  • Weekly report with a smart next-meal suggestion
  • Clean Tomato + Basil design with a raised Scan button

What you get

Full Android Studio source code, PHP admin panel and APIs, MySQL database with sample data, model training notebook, project report (47 pages), abstract, explanation with viva questions, setup guide, diagrams and screenshots.

Who can use it

Final-year students of BCA, MCA, B.Tech, BE, B.Sc IT and M.Sc IT, and anyone learning Android with machine learning.

FAQ

Does the model need internet? No, detection runs on the phone. Internet is used only to save data to the server. Can I add more dishes? Yes. Add them in the admin food database, and retrain the model with the included notebook if you want them detected from photos. Which database is used? MySQL with a PHP backend running on XAMPP.

Who can take it

  • Diploma (Polytechnic) · best fit
  • MCA · best fit
  • BE / B.Tech · best fit

Branches: Computer Science & Engineering (CSE), Information Technology (IT)

We make it easy for you

  • 1-on-1 session on AnyDesk or Google Meet
  • We install the full project on your laptop
  • We explain the flow, modules and database for your viva
  • Report and step-by-step setup guide included
  • WhatsApp help whenever you get stuck

What you get

Everything unlocks in My projects right after payment.

  • Source codeComplete, working source code
  • Project reportEditable report / documentation
  • Setup guideStep-by-step installation guide

Included free with this project

1-on-1 setup session on AnyDesk or Google Meet

After you buy, we schedule a session at a time that suits you. Our developer installs the complete project on your own laptop, runs it with you and explains it — so you can present it with confidence.

  1. 1

    Pick a time

    We call or WhatsApp you to fix the slot

  2. 2

    We install it

    Full setup on your system over AnyDesk

  3. 3

    We explain it

    Flow, modules and database on Google Meet

Modules inside

17 working modules — each one is explained in the report.

  • Meal photo recognition of 25 Indian dishes with on-device TFLite model
  • Top-3 dish suggestions with confidence score
  • Calories, protein, carbs and fat per portion
  • Manual food search and custom food entry
  • Daily diary with breakfast, lunch, snacks and dinner
  • Personal calorie and macro target (BMI, BMR, TDEE)
  • Progress charts – weekly calories, weight trend, macro split
  • Water and weight tracking
  • Streaks, points and 9 badges
  • Nutrition quiz with 20 questions
  • Weekly report with next-meal suggestion
  • Dietitian role – client requests, meal review and advice
  • Notifications and admin notices
  • Admin panel – users, dietitian approval, foods, categories, meals, quiz, badges, reports, settings
  • Admin dashboard with charts (scan vs manual meals, top dishes)
  • Secure login with hashed passwords and prepared statements
  • Model training notebook for Google Colab included

Technology used

Built with
Android (Java)Android StudioMaterial ComponentsVolleyTensorFlow Lite 2.14 (MobileNetV2 CNN)PHP 8 (PDO)MySQLXAMPPPython (TensorFlow/Keras for model training)Google Colab
Runs as
Android + Web API
Setup time
2 Hour with the guide
Documents
Project Report (47 pages, Word) with TOC, list of figures and tables, Project Abstract (Word + PDF), Project Explanation with 20 viva questions (Word + PDF), Setup Guide (Word + PDF), 16 diagrams – DFD, ER, use case, class, sequence, activity, architecture, Model training notebook and README, App mockups and admin panel screenshots

How buying works

  1. 1

    Read the free abstract

    Sign in and download it (3 per day)

  2. 2

    Pay securely

    UPI, card or net banking

  3. 3

    Download instantly

    Source code and report in My projects for 8 months

  4. 4

    1-on-1 setup session

    We install it on your laptop and explain it

How to run it

An overview — the full guide comes with the project, and we help you if anything doesn’t start.

  1. 1Install XAMPP and start Apache and MySQL.
  2. 2Copy the folder 33-nutri-snap to C:\xampp\htdocs\academic-projects\
  3. 3Open phpMyAdmin, create database android_nutri_snap and import Database/android_nutri_snap.sql
  4. 4Open the admin panel at http://localhost/academic-projects/33-nutri-snap/admin/ and log in with admin@nutrisnap.in / admin123
  5. 5Train the model in Google Colab using Model_Training/NutriSnap_Model_Training.ipynb and copy food_model.tflite to app/src/main/assets/
  6. 6Open Android_App/NutriSnap in Android Studio and let Gradle sync.
  7. 7In AppConfig.java, set BASE_URL to your PC's IP address (e.g. http://192.168.1.5/).
  8. 8Run the app on a phone on the same Wi-Fi and log in with priya.sharma@gmail.com / user123.

Questions about Food Calorie Estimation from Image

What do I get when I buy Food Calorie Estimation from Image?

Complete source code, the database, project report (47 pages, word) with toc, list of figures and tables, project abstract (word + pdf), project explanation with 20 viva questions (word + pdf) and help to run it on your laptop. Files unlock in your dashboard right after payment.

Can I see the abstract before buying?

Yes. Sign in and download the free abstract from this page, and check it with your guide first.

Will you help me run and explain the project?

Yes. After you buy, we schedule a 1-on-1 session on AnyDesk or Google Meet. Our developer installs the complete project on your own laptop, runs it with you and explains the flow, modules and database so you are ready for your viva.

Can the project be changed for my college?

Small changes such as adding a module or changing fields are possible. Tell us before you pay and we will confirm what we can do and the cost.

Which courses is Food Calorie Estimation from Image suitable for?

It suits Diploma (Polytechnic), MCA, BE / B.Tech students from Computer Science & Engineering (CSE) and Information Technology (IT).

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