Run an Arm AI Portal image segmentation model on Android
Introduction
Prepare the Android command-line tools
Build and install the image-segmentation application on an Arm-based Android phone
Run MobileSAM with ExecuTorch on Android
(Optional) Use an Arm AI Portal model without a validated adapter
Next Steps
Run an Arm AI Portal image segmentation model on Android
Who is this for?
This Learning Path is for Android and machine learning developers who want to run an optimized image-segmentation model locally on an Arm-based Android phone.
What will you learn?
Upon completion of this Learning Path, you will be able to:
- Prepare the Android command-line tools and connect an Arm-based Android phone
- Download and run the MobileSAM ExecuTorch model from the Arm AI Portal
- Understand how the Android adapter validates, prepares, and renders MobileSAM results
- Optionally inspect another image model before implementing a model-specific adapter
Prerequisites
Before starting, you will need the following:
- A macOS, Linux, or Windows development computer with Git, Python 3, and Java 17 or later
- An Arm-based Android phone running Android 9 or later
- A Hugging Face account
- A data-capable USB cable
- Basic familiarity with terminal commands and Android applications
Summary
This summary was drafted with an approved AI-assisted workflow and reviewed by Arm contributors before publication. Human technical review remains part of the process so the final page reflects engineering rigor, accuracy, and Arm editorial standards.
Frequently asked questions
These FAQs were drafted with an approved AI-assisted workflow and reviewed by Arm contributors before publication. Human technical review remains part of the process so the final page reflects engineering rigor, accuracy, and Arm editorial standards.
adb devices -l. The output should list the device with its serial and show it as authorized. If it reports unauthorized, unlock the phone and accept the debugging prompt. On Windows, you might also need the phone manufacturer’s USB driver.mobile_sam_raspberry_executorch_optimized.pte. Copy it into the directory named by the MobileSAM catalog entry under application-private storage, and start the application. Select Load model, choose an image, and select Run segmentation to generate the mask.