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:
- 12 o'clock is upward.
- 3 o'clock is upward.
- 6 o'clock is upward.
- 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 intotensor_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) intotensor_sink
Screenshot
The results of the search are