aiml_demos.xml

<?xml version="1.0" ?>
<demos xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:noNamespaceSchemaLocation="http://www.silabs.com/ss/Demo.ecore">
  <demo name="brd2601b.demo.ml_blink" label="AI/ML - Blink Demo">
    <property key="demos.blurb" value="AI/ML - Blink Demo"/>
    <property key="core.partCompatibility" value=".*efr32.g2[468].*"/>
		<property key="core.boardCompatibility" value="brd2601b"/>
		<property key="demos.imageFile" value="asset://extension.aiml_2.0.0/demos/brd2601b/ml_blink.s37"/>
    <property key="core.readmeFiles" value="examples/ml_blink/readme.md"/>
    <property key="filters" value="Device\ Type|SoC MCU|32-bit\ MCU Project\ Difficulty|Advanced Capability|Machine\ Learning"/>
		<property key="core.quality" value="PRODUCTION"/>
    <description>
      This application demonstrates a model trained to replicate a sine function.
      The model is continuously fed with values ranging from 0 to 2pi, and the
      output of the model is used to control the intensity of an LED.
    </description>
  </demo>

  <demo name="brd2601b.demo.ml_magic_wand" label="AI/ML - Magic Wand Demo">
    <property key="demos.blurb" value="AI/ML - Magic Wand Demo"/>
    <property key="core.partCompatibility" value=".*efr32.g2[468].*"/>
		<property key="core.boardCompatibility" value="brd2601b"/>
		<property key="demos.imageFile" value="asset://extension.aiml_2.0.0/demos/brd2601b/ml_magic_wand.s37"/>
    <property key="core.readmeFiles" value="examples/ml_magic_wand/readme.md"/>
    <property key="filters" value="Device\ Type|SoC MCU|32-bit\ MCU Project\ Difficulty|Advanced Capability|Machine\ Learning"/>
		<property key="core.quality" value="PRODUCTION"/>
    <description>
      This application demonstrates a model trained to recognize various hand gestures
      with an accelerometer. The detected gestures are printed to the serial port.
    </description>
  </demo>

  <demo name="brd2601b.demo.ml_model_profiler" label="AI/ML - Model Profiler Demo">
    <property key="demos.blurb" value="AI/ML - Model Profiler Demo"/>
    <property key="core.partCompatibility" value=".*efr32.g2[468].*"/>
		<property key="core.boardCompatibility" value="brd2601b"/>
		<property key="demos.imageFile" value="asset://extension.aiml_2.0.0/demos/brd2601b/ml_model_profiler.s37"/>
    <property key="core.readmeFiles" value="examples/ml_model_profiler/readme.md"/>
    <property key="filters" value="Device\ Type|SoC MCU|32-bit\ MCU Project\ Difficulty|Advanced Capability|Machine\ Learning"/>
		<property key="core.quality" value="PRODUCTION"/>
    <description>
      This application profiles a ML model. The ML model is loaded as a byte array
      which is generated from a Tensorflow tflite model file. Profiling is performed
      by running one inference with the model.
    </description>
  </demo>

  <demo name="brd2601b.demo.ml_voice_control_light" label="AI/ML - Voice Control Light Demo">
    <property key="demos.blurb" value="AI/ML - Voice Control Light Demo"/>
    <property key="core.partCompatibility" value=".*efr32.g2[468].*"/>
		<property key="core.boardCompatibility" value="brd2601b"/>
		<property key="demos.imageFile" value="asset://extension.aiml_2.0.0/demos/brd2601b/ml_voice_control_light.s37"/>
    <property key="core.readmeFiles" value="examples/ml_voice_control_light/readme.md"/>
    <property key="filters" value="Device\ Type|SoC MCU|32-bit\ MCU Project\ Difficulty|Advanced Capability|Machine\ Learning"/>
		<property key="core.quality" value="PRODUCTION"/>
    <description>
      This application uses TensorFlow Lite for Microcontrollers to detect the spoken
      words 'on' and 'off' from audio data recorded on the microphone in a Micrium OS
      kernel task. The detected keywords are used to control an LED on the board.
    </description>
  </demo>

  <demo name="brd2601b.demo.ml_audio_classifier" label="AI/ML - Audio Classifier Demo">
    <property key="demos.blurb" value="AI/ML - Audio Classifier Demo"/>
    <property key="core.partCompatibility" value=".*efr32.g2[468].*"/>
		<property key="core.boardCompatibility" value="brd2601b"/>
		<property key="demos.imageFile" value="asset://extension.aiml_2.0.0/demos/brd2601b/ml_audio_classifier.s37"/>
    <property key="core.readmeFiles" value="examples/ml_audio_classifier/readme.md"/>
    <property key="filters" value="Device\ Type|SoC MCU|32-bit\ MCU Project\ Difficulty|Advanced Capability|Machine\ Learning"/>
		<property key="core.quality" value="PRODUCTION"/>
    <description>
      This application uses TensorFlow Lite for Microcontrollers to classify
      audio data recorded on the microphone in a Micrium OS kernel task.
      The classification is used to control a LED on the board.
    </description>
  </demo>

</demos>