This is an app that continuously detects the body parts in the frames seen by your device's camera. These instructions walk you through building and running the demo on an Android device. Camera captures are discarded immediately after use, nothing is stored or saved.

The app demonstrates how to use 3 models:

• Posenet
• Movenet Lightning
• Movenet Thunder

See this blog post for a comparison between these models.

• If you don't have it already, install Android Studio 3.2 or later, following the instructions on the website.

• Android device and Android development environment with minimum API 21.

• Open Android Studio, and from the Welcome screen, select Open an existing Android Studio project.

• From the Open File or Project window that appears, navigate to and select the lite/examples/pose_estimation/android directory from wherever you cloned the tensorflow/examples GitHub repo. Click OK.

• If it asks you to do a Gradle Sync, click OK.

• You may also need to install various platforms and tools, if you get errors like Failed to find target with hash string 'android-21' and similar. Click the Run button (the green arrow) or select Run > Run 'android' from the top menu. You may need to rebuild the project using Build > Rebuild Project.

• If it asks you to use Instant Run, click Proceed Without Instant Run.

• Also, you need to have an Android device plugged in with developer options enabled at this point. See here for more details on setting up developer devices.

Downloading, extraction and placement in assets folder has been managed automatically by download.gradle.

If you explicitly want to download the model, you can download it from here:

• Posenet
• Movenet Lightning
• Movenet Thunder

Please do not delete the assets folder content. If you explicitly deleted the files, then please choose Build > Rebuild from menu to re-download the deleted model files into assets folder.