Ever since I wrote the first PyImageSearch tutorial on installing OpenCV + Python on the Raspberry Pi B+ back in February 2015 it has been my dream to offer a downloadable, pre-configured Raspbian .img file with OpenCV pre-installed.
Today this dream has become a reality.
I am pleased to announce that both the Quickstart Bundle and Hardcopy Bundle of Practical Python and OpenCV now ship with a downloadable Raspbian .img files that come with OpenCV pre-configured and pre-installed.
There are two files included:
- Raspberry Pi 3B+/3B (3.07GB)
- Raspberry Pi Zero W (2.48GB)
All you have to do is download the .img files, flash the appropriate one to your SD card, and boot your Pi.
From there, you’ll have a complete Python + OpenCV development environment at your fingertips, all without the hassle of configuring, compiling, and installing OpenCV.
To learn more about the Raspbian .img files, keep reading.
Raspbian + OpenCV out-of-the-box
I went back to my recent tutorials on installing OpenCV on the Raspberry Pi and computed the amount of time it takes to perform each step.
You know what I found?
Even if you know exactly what you are doing it can take over 2.2 hours to compile and install OpenCV on your Raspberry Pi 3B+.
Are you wondering how long the process takes for the Raspberry Pi Zero W?
I’m willing to bet that the compile + install process alone takes about 14 hours.
I then emailed a sample of novice readers who successfully installed OpenCV on their Pi and asked how long it took them to complete the compile and installation process.
Perhaps not surprisingly I found the amount of time for novice readers to install OpenCV on their Raspberry Pi jumped nearly 4x to over 8.7 hours (even longer for the Zero W).
Clearly, the barrier to entry for many PyImageSearch readers trying to learn OpenCV and computer vision is getting OpenCV itself installed on their Raspberry Pi.
In an effort to help these readers get the most out of their Raspberry Pi, I have decided to release my own personal Raspbian .img files that have OpenCV pre-configured and pre-installed.
By bundling the pre-configured Raspbian .img together with Practical Python and OpenCV my goal is to:
- Jumpstart your computer vision education by skipping the tedious process of installing OpenCV + Python on your Raspberry Pi.
- Provide you with my book, Practical Python and OpenCV, the best introduction to the world of computer vision and image processing that you can possibly get.
Of course, I will continue to create, support, and provide help to any PyImageSearch reader who is using the many free tutorials I offer on installing OpenCV + Python on the Raspberry Pi.
Again, this pre-configured Raspbian .img is intended for PyImageSearch readers who want to save time and jumpstart their computer vision education.
If this doesn’t sound like you, no worries, I totally understand — I’ll be still be providing free tutorials to help you get OpenCV up and running on your Raspberry Pi.
Raspbian + OpenCV pre-configured and pre-installed
The rest of this document describes how to install and use the Raspbian pre-configured .img file included in your purchase of the Quickstart Bundle or Hardcopy Bundle of Practical Python and OpenCV.
Note: The pre-configured Raspbian + OpenCV .img file is not included in the Basic Bundle.
At the end of this guide, you’ll also find answers to frequently asked questions regarding the Raspbian + OpenCV .img file. If you have a question that is not covered in FAQ, please send me a message.
Download and unpack the archive
After downloading your Quickstart Bundle or Hardcopy Bundle unzip the Raspbian.zip file using your favorite unarchiving utility:
After unzipping you should see the .img file similar to the screenshot above.
Write OS image to SD card using Etcher
This Raspbian .img will work on 8GB, 16GB, and 32GB SD cards. I have not tested cards larger than 32GB at this time as I do not currently own a card that large. A 4GB card is too small.
To write the pre-configured Raspbian .img to your card simply follow the official Raspberry Pi documentation. At the time of this update (2018 Aug 4), the current recommended tool is Etcher and it works with Mac, Linux, and Windows.
It even can handle compressed files such as .gz or .zip (no need to extract the .img before loading into Etcher).
Booting your Pi for the first time
After writing the the Raspbian .img to your card, insert the card into your Pi and boot it up. On the first boot, your Raspbian filesystem needs to be expanded to fit the SD card.
This means that you have to run raspi-config => Advanced => Expand Filesystem manually.
After the expansion has completed your Pi will reboot and you will be able to use it as normal (the expansion of the filesystem is only necessary on the first boot).
Here is a screenshot of the disk utilization on my Pi after it has been auto-expanded:
Notice that my entire 16GB card is available and 29% is in use.
Using Python and OpenCV on your Raspberry Pi
In order to get OpenCV 3 installed with both Python 2.7 and Python 3 bindings I leveraged Python virtual environments. Each Python virtual environment is totally independent from one another ensuring there are no dependency or versioning issues.
In the remainder of this section, I explain (1) what Python virtual environments are and (2) how to access the OpenCV + Python 2.7/Python 3 bindings.
What are Python virtual environments?
At the very core, Python virtual environments allow us to create isolated, independent environments for each of our Python projects. This implies that each project can have its own set of dependencies, regardless of which dependencies another project has.
In the context of OpenCV, this allows us to have one virtual environment for Python 2.7 and then another virtual environment for Python 3. Furthermore, each of these virtual environments can be cloned and have their own set of dependencies for a given project.
For a detailed look at Python virtual environments please refer to this tutorial.
Accessing the Python 2.7 + OpenCV 3 environment
To access the Python 2.7 + OpenCV 3 virtual environment you need to run two commands:
$ source ~/.profile
$ workon py2cv3
The source ~/.profile command loads any PATH configurations from your ~/.profile file. The workon py2cv3 accesses the Python 2.7 + OpenCV 3 virtual environment.
Conveniently, when you boot up your Pi you’ll notice that I have included a single script that you can use to setup your development environment in your home directory:
$ source start_py2cv3.sh
This command will execute both the source and workon commands for you. After executing it your shell will look like this:
Notice how the text (py2cv3) appears before your shell. This implies that you are in the py2cv3 virtual environment. This command only needs to be executed once for each shell that you open up.
Accessing the Python 3 + OpenCV 3 environment
Similar to the section above, the Python 3 + OpenCV 3 environment can also be accessed using the source and workon commands:
$ source ~/.profile
$ workon py3cv3
You can also just use the following command located in your home directory:
$ source start_py3cv3.sh
This command only needs to be executed once for each shell you open up. After executing it you’ll notice that the text (py3cv3) now appears before the prompt indicating that you have access to Python 3 + OpenCV 3:
Executing code from Practical Python and OpenCV on your Raspberry Pi
There are multiple methods to access the Practical Python and OpenCV source code on your Pi. The first is to use Chromium, Raspbian’s built-in web browser to download the .zip archive(s):
You may also use your favorite SFTP/FTP client and transfer the code from your system to your Pi:
Or you may want to manually write the code on the Pi using the built-in text editor as you follow along with the book:
I would suggest either downloading the Practical Python and OpenCV source code via web browser or using SFTP/FTP as this also includes the datasets utilized in the book as well. However, manually coding along is a great way to learn and I highly recommend it!
X11 forwarding with your Raspberry Pi
If you know how to use SSH then you can utilize X11 forwarding to access your Raspberry Pi. Simply provide the -X switch when SSH’ing into your Pi, like this:
$ ssh -X pi@your_ip_address
You will then be able to execute Python examples that utilize cv2.imshow and see the results on your laptop/desktop screen.
However, your X11 session will timeout/close so if you see the following error message:
WARNING **: Could not open X display
Unable to init server: Could not connect: Connection refused
Gtk-WARNING **: cannot open display: localhost:10.0
Then simply close your SSH connection and re-connect.
Note: Mac users may first need to install XQuartz to utilize X11 forwarding. Windows users should check their respective SSH client documentation for instructions on how to use X11 forwarding.
Frequently Asked Questions (FAQ)
In this section, I detail the answers to frequently asked questions regarding the Raspberry Pi .img file.
Which Raspbian images are compatible with which respective hardware?
Here is the compatibility listing:
- Raspberry Pi 3
- Raspberry Pi 3B+
- Raspberry Pi Zero W
I do not recommend trying with the Raspberry Pi 2 or the Raspberry Pi Zero (non-W).
What if I want to install OpenCV + Python on my Raspberry Pi by myself?
By all means, I encourage you to do so. It’s a great exercise and you’ll learn a lot about the Linux environment. I would suggest you follow one of my many free tutorials on installing OpenCV + Python your Raspberry Pi.
Again, this pre-configured Raspbian image is intended for readers who want to skip the install process and jumpstart their education.
How long will it take to install Python + OpenCV by hand?
I’ve ran the numbers and even if you know exactly what you are doing it will take a bare minimum of 2.2 hours to compile and install OpenCV on a Raspberry Pi 3B+ and approximately 14 hours on the Raspberry Pi Zero W.
If you have never installed OpenCV before or you are not familiar with Linux-based environments that number can easily jump to many times those numbers based on my survey of novice readers who successfully installed OpenCV on their Raspberry Pi.
In fact, to install everything on the Raspberry Pi Zero W including 2 environments (2 compiles of OpenCV) it took approximately 6 days (without babysitting the process overnight).
It really comes down to how much you value your time and how quickly you want to get started learning computer vision. I always encourage you to use my free tutorials on installing OpenCV on the Raspberry Pi, but if you want to save yourself time (and headaches), then definitely consider going with the pre-configured Raspbian .img.
Which Practical Python and OpenCV bundles is the Raspbian image included in?
The pre-configured Raspbian image is included in both the Quickstart Bundle and Hardcopy Bundle of Practical Python and OpenCV. The pre-configured Raspbian image is not included in the Basic Bundle.
After installing your distribution of Raspbian, how do I access Python + OpenCV?
See the “Using Python and OpenCV on your Raspberry Pi” section above.
Is Wolfram’s Mathematica included in your Raspbian distribution?
No, I am not legally allowed to distribute a modified version of Raspbian (that is part of a product) with Mathematica installed.
How did you reduce the size of the Raspbian image file?
To start, I removed unneeded software such as Wolfram’s Mathematica and LibreOffice. Removing these two pieces of software alone saved nearly 1GB of space.
From there, the size of the main partition was reduced.
Which Operating System version of Raspbian is included?
The Raspberry Pi 3B/3B+ image runs Raspbian Stretch.
The Raspberry Pi Zero W runs Raspbian Jessie due to better compatibility with OpenCV (I learned the hard way and I want you to use my images to save the headaches and frustrations I encountered).
What Python packages are installed on the Raspberry Pi?
After accessing either the respective py2cv3 or py3cv3 virtual environments run pip freeze to see a full list of Python packages installed.
In short, I have included all necessary Python packages you will need to be successful executing the examples in Practical Python and OpenCV, including OpenCV, NumPy, SciPy, scikit-learn, scikit-image, mahotas, and many others.
Update: On the Raspberry Pi 3B/3B+ image, I’ve also installed TensorFlow and Keras for deep learning on the Raspberry Pi. I also installed the Dropbox API among other packages. The ARMv6 processor in the Pi Zero W does not support TensorFlow, so neither TensorFlow nor Keras are installed.
Where can I learn more about Python virtual environments?
Where can I purchase a copy of Practical Python and OpenCV?
To purchase your copy of Practical Python and OpenCV, simply click here, select your bundle (I recommend either the Quickstart Bundle or the Hardcopy Bundle), and checkout.
I have another question.
If you have a question not listed in this FAQ, please send me a message.
To purchase your copy of Practical Python and OpenCV, just use this link.
You will find the pre-configured Raspbian .img files inside both the Quickstart Bundle and the Hardcopy Bundle (the Basic Bundle does not include the Rasbpian .img).