/fritz-android-tutorials

A collection of experiences utilizing machine learning models with Fritz

Primary LanguageJava

Examples for Android

Codeship Status for fritzlabs/fritz-sdk-android Twitter

Fritz is the machine learning platform for iOS and Android developers. Sign up for a free account to see how you can include machine learning features in your app.

Vision API: Prebuilt models that you can simply drop into your apps:

Custom Models: Deploy, Monitor, and Update your own models:

We currently support both TensorFlow Lite (code) and TensorFlow Mobile (code) for Android.

Example Apps

If you are new to Fritz, I'd recommend getting started with our Heartbeat Demo App. You can also install the latest version from the Google Play Store:

  • Heartbeat Demo App - Our kitchen sink project showcases all on-device Vision APIs and Custom Model usage.
  • Camera Boilerplate App - Our lightweight camera app to quickly get started implementing features with the camera.
  • Background Replacement App [People Segmentation] - An example app to replace the background of portraits (tutorial).
  • Sky Animation App [Sky Segmentation] - A simple photo app that replaces the sky with an animation. (Tutorial coming soon)
  • Hair Coloring App [Hair Segmentation] - An example app to replace a user's hair color (tutorial).
  • Pet Monitoring App [Object Detection] - An example app to track dogs and cats with the camera (tutorial).
  • Pet Sticker App [Pose Estimation] - Create a sticker from photos of your pets. (Tutorial coming soon)
  • Pose Estimation App [Pose Estimation] - Track body movements and position with Pose Estimation (tutorial).

Latest SDK version

  • Fritz Android SDK 3.3.1

Official Documentation

SDK Documentation

Android API Docs

Help

For any questions or issues, you can:

  • Submit an issue on this repo
  • Go to our Help Center
  • Message us directly in Slack