In the realm of cutting-edge technology, gesture recognition is gaining momentum thanks to innovative sensors like the TI AWR1642. This blog will guide you through the processes of setting up and using this sensor for recognizing various gestures such as swipes, spins, and letters.

Getting Started

Before diving into the gesture recognition magic, ensure you have the necessary components ready.

Dependencies

• Python 3.8+
• Unzip (optional)
• Curl (optional)

The unzip and curl commands are utilized by the fetch script, so having these handy can save you some gymnastics!

Installation Instructions

To install the mmwave_gesture package locally, follow these steps:

git clone https://github.com/vilari-mickopf/mmwave-gesture-recognition.git
cd mmwave-gesture-recognition
pip install -e .

With your setup ready, let’s fetch the data and models needed for gesture recognition.

Downloading Data and Models

Running the fetch script, you can download and extract:

• Data (20k samples – ~120Mb)
• Models (Conv1D, Conv2D, ResNet, LSTM, Transformer – ~320Mb)

Ensure to manually extract the downloaded data into the appropriate directories, which should resemble the structure specified in the installation instructions.

Understanding the Code – An Analogy

Imagine you are the maestro of an orchestra. Each model you choose (Conv1D, LSTM, etc.) is like selecting different instruments to create a symphony. Some instruments are better for certain sounds—like a drumbeat for rhythm or a violin for melody—just as some models are superior for specific tasks in gesture recognition. Whether you’re swiping left or deciphering the letter ‘Z’, the correct model allows your ‘orchestra’ of data and algorithms to perform beautiful music in the world of machine learning.

Setting Serial Permissions

Before PLCs (Programmable Logic Controllers) can sing their song, we need to set permissions. The exact group names may differ based on your distribution. Here’s how to do it:

gpasswd -a username uucp

For Ubuntu, use:

gpasswd -a username dialout

Remember, your changes will take effect the next time you log in!

Flashing Firmware

The latest firmware will help your sensor recognize gestures effectively. Follow these steps:

1. Close SOP0 and SOP2, then reset the power.
2. Execute the flash command:

python mmwave-console.py flash xwr16xx_mmw_demo.bin

3. Lastly, remove SOP0 and reset the power again.

Running the Setup

With your firmware properly flashed, it’s time to run the system. The console will find the ports if the board is connected before startup. If not, use the autoconnect command.

python mmwave-console.py plot predict

Use Ctrl-C to stop this process when you’re done.

Collecting Data

Collecting gesture samples necessitates effortlessly using the console commands. Here’s how:

python mmwave-console.py log up

If no gestures are captured within half a second, your logging will end automatically.

Training the Model

Initiate the training process with the following command:

python mmwave-console.py train

Troubleshooting Common Issues

• If you encounter permission errors, ensure you have included your user in the appropriate group as mentioned above.
• For issues connecting to the console, check that your board is properly connected and powered.
• If you see a red prompt, this indicates that no board connection is established—double-check your device connections.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Final Thoughts

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.