How to install OpenCV 3 on Raspbian Jessie

A few weeks ago Raspbian Jessie was released, bringing in a ton of new, great features.

However, the update to Jessie also broke the previous OpenCV + Python install instructions for Raspbian Wheezy:

• Install OpenCV 2.4 with Python 2.7 bindings on Raspbian Wheezy.
• Install OpenCV 3.0 with Python 2.7/Python 3+ bindings on Raspbian Wheezy.

Since PyImageSearch has become the online destination for learning computer vision + OpenCV on the Raspberry Pi, I decided to write a new tutorial on installing OpenCV 3 with Python bindings on Raspbian Jessie.

As an additional bonus, I’ve also included a video tutorial that you can use to follow along with me as I install OpenCV 3 on my own Raspberry Pi 2 running Raspbian Jessie.

This video tutorial should help address the most common questions, doubts, and pitfalls that arise when installing OpenCV + Python bindings on the Raspberry Pi for the first time.

Assumptions

For this tutorial I am going to assume that you already own a Raspberry Pi 2 with Raspbian Jessie installed. Other than that, you should either have (1) physical access to your Pi 2 and can open up a terminal or (2) remote access where you can SSH in. I’ll be doing this tutorial via SSH, but as long as you have access to a terminal, it really doesn’t matter.

The quick start video tutorial

Before we get this tutorial underway, let me ask you two quick questions:

1. Is this your first time installing OpenCV?
2. Are you just getting started learning Linux and how to use the command line?

If you answered yes to either of these questions, I highly suggest that you watch the video below and follow along with me as a guide you step-by-step on how to install OpenCV 3 with Python bindings on your Raspberry Pi 2 running Raspbian Jessie:

Otherwise, if you feel comfortable using the command line or if you have previous experience using the command line, feel free to follow the tutorial below.

Installing OpenCV 3 on Raspbian Jessie

Installing OpenCV 3 is a multi-step (and even time consuming) process requiring you to install many dependencies and pre-requisites. The remainder of this tutorial will guide you step-by-step through the process.

To make the installation process easier, I’ve included timings for each step (when appropriate) so you know when to stick by your terminal, grab a cup of coffee, or go for a nice long walk.

If you’re an experienced Linux user or have already installed OpenCV on a Raspberry Pi (or another other system) before, you can likely just follow the steps outlined below.

However, if this is your first time installing OpenCV (or you don’t have much prior exposure to the Linux operating systems and the command line), I highly recommend that you watch the video above and follow along with me as I show you how to install OpenCV 3 on your Rasberry Pi running Raspbian Jessie.

That said, let’s get started installing OpenCV 3.

Step #1: Install dependencies

The first thing we should do is update and upgrade any existing packages, followed by updating the Raspberry Pi firmware.

$ sudo apt-get update
$ sudo apt-get upgrade
$ sudo rpi-update

Timing: 3m 33s

You’ll need to reboot your Raspberry Pi after the firmware update:

$ sudo reboot

Now we need to install a few developer tools:

$ sudo apt-get install build-essential git cmake pkg-config

Timing: 51s

Now we can move on to installing image I/O packages which allow us to load image file formats such as JPEG, PNG, TIFF, etc.:

$ sudo apt-get install libjpeg-dev libtiff5-dev libjasper-dev libpng12-dev

Timing: 42s

Just like we need image I/O packages, we also need video I/O packages. These packages allow us to load various video file formats as well as work with video streams:

$ sudo apt-get install libavcodec-dev libavformat-dev libswscale-dev libv4l-dev
$ sudo apt-get install libxvidcore-dev libx264-dev

Timing: 58s

We need to install the GTK development library so we can compile the

highgui

$ sudo apt-get install libgtk2.0-dev

Timing: 2m 48s

Various operations inside of OpenCV (such as matrix operations) can be optimized using added dependencies:

$ sudo apt-get install libatlas-base-dev gfortran

Timing: 50s

Lastly, we’ll need to install the Python 2.7 and Python 3 header files so we can compile our OpenCV + Python bindings:

$ sudo apt-get install python2.7-dev python3-dev

Step #2: Grab the OpenCV source code

At this point we have all of our prerequisites installed, so let’s grab the

3.0.0

3.0.0

$ cd ~
$ wget -O opencv.zip https://github.com/Itseez/opencv/archive/3.0.0.zip
$ unzip opencv.zip

Timing: 2m 29s

Fur the full install of OpenCV 3 (which includes features such as SIFT and SURF), be sure to grab the opencv_contrib repo as well. (Note: Make sure your

opencv

opencv_contrib

opencv

opencv_contrib

$ wget -O opencv_contrib.zip https://github.com/Itseez/opencv_contrib/archive/3.0.0.zip
$ unzip opencv_contrib.zip

Timing: 1m 54s

Step #3: Setup Python

The first step in setting up Python for our OpenCV compile is to install

pip

$ wget https://bootstrap.pypa.io/get-pip.py
$ sudo python get-pip.py

Timing: 26s

I’ve discussed both virtualenv and virtualenvwrapper many times on the PyImageSearch blog before, especially within these installation tutorials. Installing these packages is certainly not a requirement to get OpenCV and Python up and running on your Raspberry Pi, but I highly recommend that you install them!

Using

virtualenv

virtualenvwrapper

Again, it’s standard practice in the Python community to use virtual environments, so I highly suggest that you start using them if you are not already:

$ sudo pip install virtualenv virtualenvwrapper
$ sudo rm -rf ~/.cache/pip

Timing: 17s

After

virtualenv

virtualenvwrapper

~/.profile

# virtualenv and virtualenvwrapper
export WORKON_HOME=$HOME/.virtualenvs
source /usr/local/bin/virtualenvwrapper.sh

You can use your favorite editor to edit this file, such as

vim

emacs

nano

/home/pi/.profile

Now that your

~/.profile

~/.profile

source

$ source ~/.profile

Note: You’ll likely need to run the

source ~/.profile

The next step is to create our Python virtual environment where we’ll be doing our computer vision work:

$ mkvirtualenv cv

The above command will create a virtual environment named

cv

If you want Python 3, run this command instead:

$ mkvirtualenv cv -p python3

Again, it’s important to note that the

cv

If you ever reboot your system, logout and log back in, or open up a new terminal, you’ll need to use the

workon

cv

$ source ~/.profile
$ workon cv

You can ensure you are in the

cv

cv

Figure 1: Make sure you see the “(cv)” text on your prompting, indicating that you are in the cv virtual environment.

Otherwise, you are not in the

cv

Figure 2: If you do not see the “(cv)” text on your prompt, then you are not in the cv virtual environment.

If this is the case, you need to run the

source

workon

Assuming that you are in the

cv

$ pip install numpy

Timing: 16m 10s

Step #4: Compile and install OpenCV

At this point, we are ready to compile OpenCV.

First, make sure you are in the

cv

$ workon cv

Followed by setting up the build:

$ cd ~/opencv-3.0.0/
$ mkdir build
$ cd build
$ cmake -D CMAKE_BUILD_TYPE=RELEASE \
	-D CMAKE_INSTALL_PREFIX=/usr/local \
	-D INSTALL_C_EXAMPLES=ON \
	-D INSTALL_PYTHON_EXAMPLES=ON \
	-D OPENCV_EXTRA_MODULES_PATH=~/opencv_contrib-3.0.0/modules \
	-D BUILD_EXAMPLES=ON ..

Before you move on to the compilation step, make sure you examine the output of CMake!

Scroll down the section titled

Python 2

Python 3

If you’re compiling OpenCV 3 for Python 2.7, then you’ll want to make sure the

Python 2

Figure 3: Ensuring that Python 2.7 will be used for the compile.

Notice how both the

Interpreter

numpy

cv

Similarly, if you’re compiling OpenCV for Python 3, then make sure the

Python 3

Figure 4: Ensuring that Python 3 will be used for the compile.

Again, both the

Interpreter

numpy

cv

In either case, if you do not see the

cv

cv

Now that our build is all setup, we can compile OpenCV:

$ make -j4

Timing: 1h 35m

The

-j4

However, if your

make

$ make clean
$ make

Using only one core will take much longer to compile, but can help reduce any type of strange race dependency condition errors when compiling.

Assuming OpenCV compiled without error, all we need to do is install it on our system:

$ sudo make install
$ sudo ldconfig

Step #5: Finishing the install

We’re almost there! Just a few more things and we’ll be 100% done.

For Python 2.7:

Provided you finished Step #4 without error, OpenCV should now be installed in

/usr/local/lib/python2.7/site-packages

$ ls -l /usr/local/lib/python2.7/site-packages/
total 1636
-rw-r--r-- 1 root staff 1675144 Oct 17 15:25 cv2.so

Note: In some instances OpenCV can be installed in

/usr/local/lib/python2.7/dist-packages

dist-packages

site-packages

cv2.so

site-packages

dist-packages

The last step here is to sym-link the OpenCV bindings into the

cv

$ cd ~/.virtualenvs/cv/lib/python2.7/site-packages/
$ ln -s /usr/local/lib/python2.7/site-packages/cv2.so cv2.so

For Python 3:

OpenCV should now be installed in

/usr/local/lib/python3.4/site-packages

$ ls /usr/local/lib/python3.4/site-packages/
cv2.cpython-34m.so

For some reason, unbeknownst to me, when compiling the Python 3 bindings the output

.so

cv2.cpython-34m.so

cv2.so

Luckily, this is an easy fix. All we need to do is rename the file:

$ cd /usr/local/lib/python3.4/site-packages/
$ sudo mv cv2.cpython-34m.so cv2.so

Followed by sym-linking OpenCV into our

cv

$ cd ~/.virtualenvs/cv/lib/python3.4/site-packages/
$ ln -s /usr/local/lib/python3.4/site-packages/cv2.so cv2.so

Step #6: Verifying your OpenCV 3 install

At this point, OpenCV 3 should be installed on your Raspberry Pi running Raspbian Jessie!

But before we wrap this tutorial up, let’s verify that your OpenCV installation is working by accessing the

cv

cv2

$ workon cv
$ python
>>> import cv2
>>> cv2.__version__
'3.0.0'

You can see a screenshot of my terminal below, indicating that OpenCV 3 has been successfully installed:

Figure 5: OpenCV 3 + Python 3 bindings have been successfully installed on my Raspberry Pi 2 running Rasbian Jessie.

Troubleshooting

Q. When I try to use the

mkvirtualenv

workon

A. Go back to Step #3 and ensure your

~/.profile

source ~/.profile

Q. After I reboot/logout/open up a new terminal, I cannot run the

mkvirtualenv

workon

A. Anytime you reboot your system, logout and log back in, or open up a new terminal, you should run

source ~/.profile

Q. When I open up a Python shell and type

import cv2

ImportError: No module named cv2

A. The reason for this error is hard to diagnose, mainly because there are multiple issues that could be causing this problem. For starters, make sure you are in the

cv

workon cv

workon

site-packages

cv

~/.virtualenvs/cv/lib/python2.7/site-packages/

~/.virtualenvs/cv/lib/python3.4/site-packages/

cv2.so

Summary

In this lesson we learned how to install OpenCV 3 with Python 2.7 and Python 3 bindings on your Raspberry Pi 2 running Raspbian Jessie. I provided timings for each step so ensure you can plan your install accordingly.

It’s also worth mentioning that I provide OpenCV v2.4 and v3 install instructions for Raspbian Wheezy in the following posts:

• Install OpenCV 2.4 with Python 2.7 bindings on Raspbian Wheezy.
• Install OpenCV 3.0 with Python 2.7/Python 3+ bindings on Raspbian Wheezy.

If you run into any issues during the installation process, please see the Troubleshooting section above. Additionally, I would suggest watching the video tutorial at the top of this post to aid you in the setup process.

Before you go…

I tend to cover a lot of great computer vision projects using OpenCV and the Raspberry Pi, so consider entering your email address in the form below to be notified when these posts go live!

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