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DeepLabV3Demo

README.md

ExecuTorch Android Demo App

This guide explains how to setup ExecuTorch for Android using a demo app. The app employs a DeepLab v3 model for image segmentation tasks. Models are exported to ExecuTorch using XNNPACK FP32 backend.

Prerequisites

  • Download and install Android Studio and SDK 34.
  • (For exporting the DL3 model) Python 3.10+ with executorch package installed.

Step 1: Export the model

Run the script in dl3/python/export.py to export the model.

Step 2: Push the model to the phone

The app loads a hardcoded model path (/data/local/tmp/dl3_xnnpack_fp32.pte) on the phone. Run the following adb command to push the model.

adb push dl3_xnnpack_fp32.pte /data/local/tmp/dl3_xnnpack_fp32.pte

Step 3: Build, install, and run the app on your phone

On your terminal

(cd dl3/android/DeepLabV3Demo first)

./gradlew installDebug
adb shell am start -W -S -n org.pytorch.executorchexamples.dl3/.MainActivity

On Android Studio

Open Android Studio and open the project path dl3/android/DeepLanV3Demo. Wait for gradle sync to complete. Then simply press "Run app" button (Control + r).

Step 4: Run unit test

On your terminal

./gradlew connectedAndroidTest

On Android Studio

In Android Studio project, open file app/src/androidTest/java/org/pytorch/executorchexamples/dl3/SanityCheck.java, and click the "Play" button for public class SanityCheck (Control + Shift + r).