How to Install & Setup OpenCV on Raspberry Pi 4

Overview
In this guide, we will learn how to
install
&
setup
OpenCV
on
Raspberry Pi 4
computer.
OpenCV
(Open Source Computer Vision Library) is an
open-source computer vision
and
machine learning
software library. It contains over 2500 optimized
algorithms
that span a wide range of areas in vision, including but not limited to:
Image and Video Capture
Preprocessing (filtering, graying, thresholding, etc.)
Face & Eyes Detection
Object Detection
Edge Detection & Motion Sensing
Image Segmentation
Machine Learning
Age & Gender Identification
3D Reconstruction
Motion Analysis and Object Tracking
Augmented Reality
OpenCV
and
Raspberry Pi
together offer a powerful platform for a wide range of
computer vision projects
. Whether you’re building a smart doorbell with face recognition, a robot that can navigate its surroundings, or simply learning the basics of computer vision, this combo is both affordable and versatile.
Requirements
For the Hardware parts, we need the following components:
S.N.
Components
Quantity
Purchase Link

Raspberry Pi 4

Amazon
SunFounder

SD Card 16/32 GB

Amazon
SunFounder

5V, 3A DC Adapter for RPi

Amazon
SunFounder

LCD Display (Optional)

Amazon
SunFounder

Mouse & Keyboard (Optional)

Amazon
SunFounder
You may use the
HDMI Monitor
or a
VNC Viewer
for the setup part.
Install & Setup OpenCV on Raspberry Pi
Before learning how to install & setup OpenCV on the Raspberry Pi Computer, you need to setup your Raspberry Pi first. To understand how to setup the Raspberry Pi first, follow this article:
Setting up Raspberry Pi
In this guide, we have used a Raspberry Pi 4 with the latest Raspbian Buster. The OpenCV installation process is divided into multiple steps as follows:
Step 1: Install dependencies

Updating Existing Packages
:
Execute the following command to update and upgrade your system’s packages:

sudo
apt
get
update
&&
sudo
apt
get
upgrade

Installing Image I/O Packages
:
For support with various image file formats, install the necessary packages using:

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

Setting Up Video I/O Packages
:
To handle different video file formats and work with video streams, use the commands below:

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

Installing the GTK Development Library
:
To compile the highgui module (used for displaying images and creating basic GUIs), install the GTK development library:

sudo
apt
get
install
libgtk2

dev

Additional Dependencies for OpenCV Optimization
:
For enhanced OpenCV operation optimization, install these extra dependencies:

sudo
apt
get
install
libatlas
base
dev
gfortran
Step 2: Installing pip (Package Management Tool)
If you haven’t installed
pip
for Python 3 yet, execute the command below:

sudo
apt
get
install
python3
pip
Step 3: Installing the Numpy Library
Numpy provides essential mathematical and numerical capabilities useful for OpenCV. If you haven’t installed it yet, use the command:

pip
install
numpy
Step 4: Accessing OpenCV on Raspbian Repository
To locate OpenCV in the default Raspbian Buster repository, use the command:

apt
list
python*
opencv*
Step 5: Installing OpenCV
Execute the following command to install OpenCV on Raspberry Pi.

sudo
apt
install
python3
opencv
Step 6: Verifying OpenCV Installation
To confirm the installation of OpenCV, use:

apt
show
python3
opencv
After executing, you should see that the latest version is successfully installed!
Conclusion
We’ve walked through the systematic process of setting up and confirming the installation of OpenCV on a Raspbian system. This foundational step is crucial for delving into computer vision projects using a Raspberry Pi. By ensuring that the correct version is installed, you’re setting the stage for a seamless experience with OpenCV. As you embark on your computer vision journey, always ensure that your software tools are up-to-date and correctly configured for optimal performance.