TensorFlow can be integrated into mobile apps for many use cases that involve one or more of the following machine learning tasks:
- Speech recognition
- Image recognition
- Gesture recognition
- Optical character recognition
- Image or text classification
- Image, text, or speech synthesis
- Object identification
To run TensorFlow on mobile apps, we need two major ingredients:
- A trained and saved model that can be used for predictions
- A TensorFlow binary that can receive the inputs, apply the model, produce the predictions, and send the predictions as output
The high-level architecture looks like the following figure:
The mobile application code sends the inputs to the TensorFlow binary, which uses the trained model to compute predictions and send the predictions back.
