KAJU: Calorie Counter & Recipes

KAJU is an app used to calculate BMI and daily calorie needs, tracks user calories, and offers over 600.000 foods and recipes.

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Introduction ⚒

KAJU: Calorie Counter & Recipes, basically KAJU helps the user to find 600.000+ recipes and foods with help of one key ingredient. Also, user can get recipes and foods with a single search. User can get the nutritional content and instructions for the food he will cook. Our motive for developing this app was to help people who are pretty confused while cooking and also want to keep track of how many of their calories come from it. We hope it will be useful to people who fight against unhealthy diets and waste a lot of time finding healthy recipes.

Steps to run ?

  • Clone or download the app from this repository. ?
  • Open project file in terminal. ?
  • Run pod install to install all dependencies. ?
  • Open the KAJU.workspace file. ?
  • Change the bundle Identifier. ⚙️
  • Press Ctrl + R to run the app. ?

How to Use ?‍?

  • As soon as the app launches you will get a register/login screen.
  • After completing the registration, enter the requested information about you.
  • We need your goal, daily activity level, sex, current age, height, and weight to accurately calculate your BMI and calorie needs.
  • After that, you can start your plan and enter foods/recipes for different lunch types.
  • Then you will get an option of a search bar, and type that one key ingredient for which you have to find food or recipe.
  • Click on the food or recipe which you found good, and you will get the whole list of ingredients, instructions, and calorie values.
  • Access the foods and recipes you have added to your favorites offline.
  • Try an egg timer for different types of boiled eggs.
  • Change your personal information and preferences from the profile page.

Libraries/Frameworks Used in Project ?

  • UIKit
  • CoreData
  • DropDown
  • Foundation
  • Toast-Swift
  • FirebaseCore
  • ValueStepper
  • CLTypingLabel
  • FirebaseStorage
  • CountdownLabel
  • FirebaseFirestore
  • IQKeyboardManagerSwift

API Used ?

  • Edamam Recipe API
  • Spoonacular Nutrition API
  • Accuracy of 96%.
  • Latency of 945ms
  • Sucess Rate 95%

Snapshots of App ?

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How to Contribute ?

  • Run the app – Steps are mentioned above.
  • If you face issues in any step open a new issue.
  • To fix issues: Fork this repository, make your changes and make a Pull Request.

GitHub

View Github