This describes how to enable and use the MLTK command-line interface.
This assumes the MLTK has been installed and is available on the command prompt.
Enable Python Virtual Environment¶
All MLTK commands are accessible via the
mltk command-line command.
mltk command expects arguments with the format:
mltk <operation> [<arguments>] [<options> ...]
<operation>- The specific operation to perform (e.g.
<arguments>- Operation-specific arguments (e.g. The name of an ML model)
<options>- Additional flags & arguments to give to the operation
All MLTK commands provide details about their supported arguments/options by appending the
--help option, e.g.:
mltk --help mltk profile --help mltk train --help
The following operations are supported by the
|profile||Profile a model to determine how efficiently is may run on hardware|
|train||Train a model and generate a
|tensorboard||Monitor/profile the training of a model using Tensorboard|
|ssh||Train a model on a remote cloud server via SSH|
|evaluate||Evaluate a trained model to determine how accurate it is|
|quantize||Quantize a trained model to reduce its memory footprint|
|summarize||Generate a text summary of a model|
|view||View a model's graph in an interactive visualizer|
|update_params||Update the parameters embedded into a generated
|view_audio||Visualize the spectrograms generated by the Audio Feature Generator|
|classify_audio||Classify real-time audio from a development board's or PC's microphone|
|classify_image||Classify images from an RGB camera connected to a development board|
|fingerprint_reader||View fingerprint images from a fingerprint module connected to a development board|
|commander||Run the Silicon Lab's Simplicity Commander utility|
To get more information about a specific operation, issue the command:
mltk <operation> --help