mmWave Industrial Visualizer User Guide

Overview

This tool parses and visualizes data sent from TI mmWave Radar devices. It is designed to help expedite evaluation and to make it easier to investigate TI radar demos.

Supported Demos

The follow TI demos are supported in this visualizer:

Out of Box Demo
3D People Counting
Overhead 3D People Counting
Long Range People Detection
Vital Signs with People Tracking
Mobile Tracker
Small Obstacle Detection

Quickstart

This section will give a brief rundown of how to get started using the mmWave Industrial Visualizer.

1. Launch the visualizer:

Navigate to <radar>\tools\visualizers\Industrial_Visualizer
Run mmWave_Industrial_Visualize.exe
It should take 5 - 10 seconds to startup.

On the left side of the visualizer setup window are options and parameters for running the demo. On the right side is a 3D graph which will display the relevant demo output.

2. Set COM Ports

At the top left of the GUI should be two text fields for the COM Ports. These will attempt to autodetect your TI mmWave Device and autofill the correct COM ports.

If this does not auto-populate, find them by going to your Device Manager (or equivalent menu for your OS) and looking for the serial ports.

Typically, the CLI COM Port will be name either * Silicon Labs Dual CP2105 USB to UART Bridge: Enhanced COM Port * XDS110 Class **Application/User UART**

Typically, the Data COM Port will be name either * Silicon Labs Dual CP2105 USB to UART Bridge: Standard COM Port * XDS110 Class Auxiliary Data Port

When entering the COM Port, please be sure to put only the COM Port number.

3. Select Demo

Now that the COM Ports are selected, using the dropdown menu in the top left to select the demo that you’d like to run. Be sure that the corresponding binary is flashed onto your device.

4. Connect to Device

Now click the connect button in the top left. If the status does not change to Connected, please return to step 1 and revalidate the COM port selections

5. Select Configuration

Next, click the Select Configuration button, and navigate using your file explorer to the correct cfg file for your application. Typically, these can be found at <Radar_Toolbox_location>/src/ti/examples/<ExampleName>/chirp_configs

6. Send Configuration and Start the Demo

Finally, click the Start and Send Configuration button, which will transmit your config file to the device. Please note that this may take ~10 seconds. Once this is complete, data should begin to be displayed in the GUI.

Getting Familiar with Different Parts of the Visualizer

Setup Pane

This area is where you will start when using the visualizer. You can configure COM Ports (if they were not detected automatically), select the demo type, and connect to the device.

Statistics Pane

This area will show some of the high level information for the data that is being shown, such as the frame number, number of points, and the number of targets/tracks (when applicable).

Configuration Pane

This area is focussed on your radar chirp configuration. You can use it to select your config file, send it to the device, or to just enable the visualizer if a Hard Coded Configuration is being used.

Plot Controls Pane

This area allows you to customize the display of information on the plot. Use it to hide targets/tracks (for demos which generate them), determine how you would like points to be colored, and how many frames worth of data to display concurrently.

Sensor Position Pane

This area allows you to input the sensor position, to ensure that the visualization matches your environment as closely as possible. The various tilt angles are measured in degrees, while sensor height is measured in meters.

Boundary Boxes Pane

This area is used to generate and build geometry into the visualization which can impact what is seen. By default, a pointBounds box will be used, which will remove any points outside of the designated region. Additional types of boxes may be added for specific labs and configurations, such as boundary boxes for tracks or occupancy zones.

3D Plot

This area is the main plot for the visualizer. It shows the relevant information which is transmitted from the device in realtime, and can be used to better understand the data being output.

Components Unique to Specific Demos

Some demos may add components to the visualizer to better enable the visualization for that specific demo. Below, you can see some of the unique options which are available.

Vital Signs Pane

This area is unique to the Vital Signs with People Tracking demo, and shows crucial vital signs of detected people via the measurements done in this demo.

Working with Visualizer Source Code

In order to ensure that the visualizer can be modified to suit any special use case, the source code for the visualizer is included.

Requirements

Below is a table which includes the required software. Most of these are python modules which can be installed with pip. You can use the script setupEnvironment.bat to install all of these using pip.

Software	Version	How to get
Python 3	3.6 or later	Python 3.6 64Bit Download
pyqt5	5.15.4	`pip install pyqt5==5.15.4`
pyopengl	3.1.5	`pip install pyopengl==3.1.5`
numpy	1.19.4	`pip install numpy==1.19.4`
pyserial	3.5	`pip install pyserial==3.5`
pyqtgraph	0.11.0	`pip install pyqtgraph==0.11.0`

Running the Visualizer From Source

Once all the requisite software is installed, the GUI can be started by running the command python gui_main.py in the terminal

Understanding the Visualizer Source Code

Below is a brief rundown of the various source files included in this visualizer and what their purpose is.

gui_main.py the main program which controls placement of all items in the GUI and schedules UART read and graphing tasks.
gui_parser.py defines an object used for parsing the UART stream. If you want to parse the UART data, you can use this file to do so.
gui_threads.py defines the different threads that are run by the demo. These threads handle updating the plot and calling the UART parser.
graphUtilities.py contains functions used to draw objects.
gui_common.py aggregates several variables and configurables which are used across several files.
parseFrame.py is responsible for parsing the frame format of incoming data.
parseTLVs.py is responsible for parsing all TLV’s which are defined in the demos.

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