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OrientationDetection


title: Orientation Detection ...

Tizen .NET (Wearable) NNStreamer Application Example - Orientation Detection

Introduction

This example passes accelerometer sensor data stream to a neural network (tensorflow-lite) via tensor_src_tizensensor gstreamer element. The neural network predicts one of four orientation of the device:

  1. 12 o'clock is upward.
  2. 3 o'clock is upward.
  3. 6 o'clock is upward.
  4. 9 o'clock is upward.

Description

  • This is a sample application using Tizen .NET for wearable device.
  • If you want to run it on your device, Tizen 6.0 or higher is required.
  • About details of NNStreamer, please check this page.
  • Used gstreamer pipeline:
    tensor_src_tizensensor (accelerometer) -- tensor_filter -- tensor_sink
    • The accelerometer measures the device's accelerometer vector in 3 axes.
    • The tensor_src_tizensensor element feeds those three float values into tensor_filter element.
    • TF-lite model orientation_detection.tflite predicts possibility of each four orientations.
    • tensor_filter element (with the TF-lite model) provides the tensor with four float values (the possibilities) into tensor_sink

Screenshot

Alt screenshot