OpenCV (Open Source Computer Vision Library) is the industry standard for image processing and computer vision. However, installing it on a Raspberry Pi 3 can be notoriously difficult. While modern versions of Python allow for a simple pip install opencv-python, compiling it from source is still often the best way to get full hardware optimization and support for extra modules.
In this guide, we provide a streamlined, “painless” workflow for installing OpenCV 3.3.0 with Python 3 support on your Pi.
Step 1: Install Dependencies
Before we touch OpenCV, we need to install the various libraries and tools that it relies on for handling images, videos, and graphical windows.
sudo apt-get update && sudo apt-get upgrade
sudo apt-get install build-essential git cmake pkg-config -y
sudo apt-get install libjpeg-dev libtiff5-dev libjasper-dev libpng12-dev -y
sudo apt-get install libavcodec-dev libavformat-dev libswscale-dev libv4l-dev -y
sudo apt-get install libxvidcore-dev libx264-dev -y
sudo apt-get install libgtk2.0-dev libatlas-base-dev gfortran -y
sudo apt-get install python2.7-dev python3-dev qtbase5-dev -y
Step 2: Download OpenCV Source Code
We need both the main OpenCV repository and the “contrib” repository, which contains experimental features.
cd ~
wget -O opencv.zip https://github.com/Itseez/opencv/archive/3.3.0.zip
unzip opencv.zip
wget -O opencv_contrib.zip https://github.com/Itseez/opencv_contrib/archive/3.3.0.zip
unzip opencv_contrib.zip
Step 3: Set Up a Virtual Environment
It is highly recommended to install OpenCV inside a virtual environment to keep your global Python installation clean.
sudo pip install virtualenv virtualenvwrapper
source ~/.profile
# Create the environment
mkvirtualenv cv -p python3
workon cv
pip install numpy
Step 4: Compiling OpenCV (The Long Part)
This is where the actual building happens. This process can take 1 to 2 hours depending on your SD card speed.
cd ~/opencv-3.3.0/
mkdir build && cd build
cmake -D CMAKE_BUILD_TYPE=RELEASE \
-D CMAKE_INSTALL_PREFIX=/usr/local \
-D INSTALL_C_EXAMPLES=OFF \
-D INSTALL_PYTHON_EXAMPLES=ON \
-D OPENCV_EXTRA_MODULES_PATH=~/opencv_contrib-3.3.0/modules \
-D BUILD_EXAMPLES=ON ..
# Start the compilation (use all 4 cores of the Pi 3)
make -j4
sudo make install
sudo ldconfig
Step 5: Verification
To ensure everything worked, activate your environment and try to import the library in Python:
workon cv
python
>>> import cv2
>>> print(cv2.__version__)
'3.3.0'
Bonus: Testing with a USB Webcam
Once installed, use this quick script to verify that OpenCV can capture video from a standard USB webcam.
import cv2
# 0 is usually the index for the first USB camera
cap = cv2.VideoCapture(0)
while True:
ret, frame = cap.read()
if not ret:
break
# Convert to grayscale for a classic CV look
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
cv2.imshow('OpenCV Test', gray)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
Conclusion
Installing OpenCV from source on a Raspberry Pi is a badge of honor for any computer vision enthusiast. You now have a high-performance environment ready for facial recognition, object tracking, and much more!
Next Steps:
Written by
Abdur-Rahmaan Janhangeer
Chef
Python author of 7+ years having worked for Python companies around the world
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