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Train and deploy machine learning models for mobile apps with Fritz.
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create_ml_playgrounds updated main readme Jan 30, 2019
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image_segmentation Fix preprocessing Mar 6, 2019
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Fritz Models

A collection of machine and deep learning models designed to run on mobile devices.

Models in this repository contain code and utilities for training models as well as converting them to mobile-friendly formats like Core ML, TensorFlow Mobile, and TensorFlow Lite.


  • Image Labeling: Label images based on their content.
  • Object Detection: Localize and label objects in an image with a bounding box.
  • Style Transfer: Transform images into works of art by transfering the style of one image onto the content of another.
  • Image Segmentation: Semantic segmentation of images. Assign a value to each pixel of an image corresponding to the type of object it belongs to.
  • Create ML Playgrounds: A series of playgrounds for training models with Apple's Create ML tool

Don't see the model you're looking for? Open an issue and let us know!

Add to your app

To see live demonstrations of these models running on-device, the Heartbeat App is available in both the App Store (source code) and Play Store (source code).

If you'd like to incorporate any of these models or versions you've trained into your own app, head over to Fritz. SDKs are available for both iOS and Android.

Additional resources

Additional, non-code resources for machine learning and AI.

Join the community

Heartbeat is a community of developers interested in the intesection of mobile and machine learning. Chat with us in Slack and stay up to date on the latest mobile ML news with our Newsletter.

A note about large files

Large files like model checkpoints, data, and archives of compiled code are managed via git lfs. You need to have Git LFS installed in order to download these files. Installation instructions are available here.

If you have Git LFS installed, large files will download automatically by default. This can take a while and require a good connection. To clone this repository without downloading the model checkpoints, you can run:

GIT_LFS_SKIP_SMUDGE=1 git clone ...
You can’t perform that action at this time.