Rename WiFi Interface on Ubuntu 20.04

During an experiment, I need to use three WiFi interfaces on a Raspberry Pi running Ubuntu 20.04. In addition to Raspberry Pi's internal WiFi interface, I added two USB WiFi adapters. Three network interfaces showed up in the system (ip link command), and they are named wlan0, wlan1, and wlan2 by default.

I often need to capture packets with tcpdump, and I often have to be type these interface names manually. It isn't easy to remember the purpose of each network interface, so I wanted to rename the interfaces to reflect their role in my application. However, this isn't as easy as it sounds.

🚫 Netplan

Ubuntu 20.04 configures network interfaces using Netplan, so my first thought was: I can write a Netplan configuration that matches network interfaces with their MAC addresses, and assigns the desired name to each network interface.

The config file would look like this:

NFD nightly APT repository

Last year, I started building NFD nightly packages in GitHub Actions. So far, installation is a manual procedure: the user must manually download the ZIP files from, decompress them, and figure out the dependency among various .deb packages. Starting today, I'm publishing NFD nightly packages in an APT repository, and you can install them with apt-get command.

Add the NFD nightly APT repository

Add the repository with the command that matches your platform:

# Ubuntu 18.04 (bionic), amd64 (laptops and servers)
echo "deb [trusted=yes] bionic main" \
  | sudo tee /etc/apt/sources.list.d/nfd-nightly.list

# Ubuntu 20.04 (focal), amd64 (laptops and servers)
echo "deb [trusted=yes] focal main" \
  | sudo tee /etc/apt/sources.list.d/nfd-nightly.list

# Debian 10 (buster), amd64 (laptops and servers)
echo "deb [trusted=yes] buster main" \
  | sudo tee /etc/apt/sources.list.d/nfd-nightly.list

# Debian 10 (buster), armv7 (Raspberry Pi 3 or 4)
echo "deb [trusted=yes] buster main" \
  | sudo tee /etc/apt/sources.list.d/nfd-nightly.list

# Debian 10 (buster), armv6 (Raspberry Pi Zero W)
echo "deb [trusted=yes] buster main" \
  | sudo tee /etc/apt/sources.list.d/nfd-nightly.list

If your operating system and CPU architecture combination is not listed, it is not supported by NFD nightly. See the previous post on how to request a new platform.

NFD nightly packages

NDN Forwarding Daemon (NFD) is the reference implementation of Named Data Networking (NDN) forwarding plane. The software is continuously developed, but binary releases happen rather infrequently. Recently, I made a workflow to build NFD and related software automatically.

Download page:


Which platform should I choose?

  • The platform identifier has two parts: Linux distribution and CPU architecture. Both parts must match your machine.
  • Linux distribution:
    • bionic is Ubuntu 18.04.
    • buster is Debian 10. This includes Raspberry Pi OS.
  • CPU architecture:

GPU Accelerated Contour Detection on PiCamera

Earlier this month, I spent a week building OpenCV 3.2.0, with the intention to reproduce the contour detection demo I witnessed at MoCoMakers meetup. I successfully made contour detection working on PiCamera through MJPEG streaming. P.S. Can you tell the Hack Arizona 2016 shirt?

contour on PiCamera

How MocoMakers's Demo Works

def makeContour(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    gray = cv2.GaussianBlur(gray, (3, 3), 0)
    edged = auto_canny(gray)

def auto_canny(image, sigma=0.33):
    v = np.median(image)
    lower = int(max(0, (1.0 - sigma) * v))
    upper = int(min(255, (1.0 + sigma) * v))
    edged = cv2.Canny(image, lower, upper)
    return edged

Their code works with a MJPEG stream from an Android phone. It extracts a JPEG frame from the video stream, processes the image through makeContour function, and displays the result. The makeContour function converts the RGB image to grayscale, blurs the grayscale image, and runs the Canny Edge Detection algorithm.

Install OpenCV 3.2.0 on Raspberry Pi Zero W in 15 Minutes

OpenCV, or Open Source Computer Vision Library, is an open source computer vision and machine learning software. It works on Raspberry Pi computers, and can process photos captured by the Raspberry Pi Camera Module.

OpenCV has two supported versions: 2.4.x and 3.x. New features are being added to 3.x branch, while 2.4.x only receives bug fixes and efficiency fixes. It is recommended that new developments should use OpenCV 3.x, to take advantage of new features. However, the official operating system for the Raspberry Pi, Raspbian Stretch, comes with OpenCV 2.4.9. While I am not yet familiar with OpenCV algorithms, one thing notably missing from OpenCV 2.4.9 is a Python 3 binding.

I wanted to have OpenCV 3 running in Raspbian Stretch on a Raspberry Pi Zero W. Unable to find existing packages for Pi Zero and Stretch, I had no choice but to compile my own OpenCV 3. I decided to do it the proper way: build a backported Debian package. This method is superior to installing from the source code, because the packages can easily be deployed to other Raspberry Pi Zero W computers. I followed the Simple Backport Creation instruction, and spent a week building the packages. Now I'm sharing my compiled packages, so that you can use them if you dare.

What You Need

The Quest of Building OpenCV 3.2.0 Debian Packages on Raspberry Pi Zero W

The newest members in my toy collection are a Raspberry Pi Zero W (paid link) and a NoIR Camera Module (paid link), purchased in Dec 2017. Recently, I witnessed an impressive Contour Detection demo at MoCoMakers meetup. I read their source code, and it has a dependency on cv2 Python package. Therefore, the first step to get it working on my RPi Zero would be installing OpenCV that provides cv2 package.

While Raspbian Stretch offers a python-opencv package, it is version 2.4.9 released in 2014, and it only works with Python 2 but not Python 3. Since I'm starting from scratch, I wanted to develop on newer platforms: OpenCV 3.x and Python 3.

Many online tutorials suggest compiling OpenCV from source code. There are also a few sites offering pre-compiled tarballs, but these are either compiled for the Raspberry Pi 3, or built for Raspbian Jessie; neither would be compatible with my Raspberry Pi Zero W running Raspbian Stretch. Therefore, I started my quest to build OpenCV 3 for Pi Zero.

Debian Package > Source Code

When I first learned Linux, the standard process of installing software is wget, tar xzvf, ./configure, make, make install. Today, this is no longer recommended because software installed this way is difficult to remove and could cause conflicts. Instead, it is recommended to install everything from Debian packages. Fast Operating System Switch for BerryBoot

BerryBoot is a bootloader for Raspberry Pi, allowing multiple operating system images to be placed on a single microSD card. It displays a menu upon system boot, so that the user can choose which OS to load.

I use a Raspberry Pi 3 as my primary desktop computer. It loads Ubuntu Mate 16.04 by default, in which I can code, read, and write dissertation. The same computer is also equipped with RetroPie, as my gaming machine playing FreeDoom.

One problem I'm frequently facing is: in order to switch from work mode to game mode, I must reboot the machine. Shutting down Ubuntu Mate can take as little as 10 seconds, or as much as 3 minutes, depending on luck. I hate to stay with the machine while it's rebooting, but if I walk away, I may miss the 10-second window in which I should select RetroPie from the BerryBoot menu, before it loads the default, Ubuntu Mate, automatically.

A less known feature of BerryBoot is its runonce file. You may instruct BerryBoot to load a specific image at next boot by writing the image name to data/runonce file in BerryBoot partition. This works particularly well if the Raspberry Pi is headless and does not have a keyboard, but it requires 5 steps and requires typing the full image name in the runonce file.

To simplify this process and quickly switch to another operating system in BerryBoot, I wrote a little script: