Whether you want to lose weight, tone up, get healthy, change your habits, or start a new diet, our app has you covered. Sign up for FREE and start living a happier and healthier life today! Just 3 steps as following:

1

Take a picture of the food

Take a simple picture of the food.
And upload it to our App.

2

Identify what kind of food it is

The AI will analysis the picture
and identify what kind of food it is.

3

Find out its calories!

The calories will be displayed on the screen within a few seconds.

TRACKING FOOD IS FAST AND EASY

■ Biggest Food Database -- 11+ million foods in our database including global items and cuisines.
■ food Scanner -- Simply take pictures to log foods. And 4+ million barcodes recognized.
■ Recipe Importer -- Easily import the nutrition information for the recipes you cook.
■ Restaurant Logging -- Quickly log menu items from your favorite restaurants.
■ Food Insights -- Learn how to make healthier choices about the foods you eat.
■ Personalized Experience -- Create your own foods, recipes, and meals and save favorites.
■ Calorie Counter -- We automatically calculate the calories in your foods, meals and recipes.
■ Macro Tracker -- We automatically calculate the macros (carbs, fat, protein) in your foods, meals and recipes.
■ Track All Nutrients -- Calories, macros (carbs, fat, protein), sugar, fiber, cholesterol, vitamins, and more.
■ Customize Your Diary -- Log breakfast, lunch, dinner and snacks or create your own meals.

Ressources to code it

To create this app, we're going to use ml5.js which is a JavaScript library about the very basics of Artifical Intelligence.
Then, we're going to use a specific function called imageClassifier() on which you can find complete documentation on the official ml5 website. This will allow the AI to recognize the content of an image.
We will also be using another library that will allow us to drop directly the picture of the food on the website, so it'sbe more convenient for the user.
1.First of all, you need to make reference to the library in your index.html file :
2.Then, you will have to create a .js file to include the code for ml5. Our ml5 code will have two essential components. One that will hold the image and another that will give the result.
Here are the ressources to the websites I think would be useful to do so: ML5.js: Webcam Image Classification