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E2E TFLite Tutorials

We would love your help! You can help by creating a TensorFlow Lite (tflite/TFLite) model ready for implementation, add a mobile app idea that needs a tflite model created, or write an end-to-end tutorial with sample code.

This is also where you can seek help from the community.

Project ideas (help needed!)

If you are interested in helping out, take a look at the potential projects below and assign an corresponding issue to yourself from the repo issue list.

Once you form a project team, move the idea to the "in progress" section below, create a new repo and link to it.

  • YOLO - overview.
  • Classify pose - overview (an example use-case can be found here).
  • A mobile application (preferably Android/iOS) demonstrating optical character recognition (refer to this Colab Notebook to see how this is done in Python).
  • A mobile application (preferably Android/iOS) demonstrating several text-to-speech models as shown in this repository.

Here are some more details on how exactly you can help:

  • Generate ideas
  • Create tflite model(s)
  • Create Colab Notebook(s) demonstrating the model creation process along with running inference in Python
  • Publish tflite model(s) optional
  • Develop Android app(s) to demonstrate the model(s)
  • Develop iOS app(s) to demonstrate the model(s)

The tutorials listed below would give you a good idea of the afore-mentioned pointers. The Contribution Guidelines provide detailed instructions on how you can contribute.

End-to-end tutorials (in progress)

Take a look at the in progress projects to see what it's like to work on a project.

End-to-end tutorials (completed)

Once a project has been completed, please open a PR to awesome-tfite to add the links of the tflite model, sample code and tutorials.

Contact the admins

This should be done via GitHub issues. Only use it when you have something relevant to discuss otherwise the issues will be automatically closed.

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