Sehat-In is an image classification app based on the MLkit and TFlite model, This project is done under the Bangkit Capstone program

• Authentication: Authentication process using the Firebase Auth
• Food Scanning: Scanning process using the CameraX + MLKit Object Detection + Inference using the TfLite model
• Food Store Recommendation: Feat not, giving your nearest recommendation location from you to buy some fruits
• Detail Fruits / Recipe Nutrients: Giving u the information about the nutrition of the food and the recommendation dish out of this scanned item

• Projects 100% Kotlin
• Using the MVVM + Navigation Architecture and using the Hilt as the Dependency Injection
• Firebase Firestore to store the favorite and history user
• Firebase Auth to handle the authentication process
• Retrofit and OkHttp for Construct the Rest API

• You can start using this app by visiting this link here
• If you're want to develop this app more, fork this repo and add the apiKey.properties within the app folder to add the apiKey for particular API, here's the examples

  RECIPE_KEY_API=... (get from the Edamam-Recipe API)
  APP_ID_RECIPE=... (get from the Edamam-Recipe API)
  WEB_CLIENT_ID=... (get from the Firebase auth console)
  MAPS_SDK_API_KEY=... (get from the Google Cloud Maps Console)
  

• Since the app is far from perfect, you can try to fork and customize as for your needs, and don't forget to make a pull request