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OpenCV Installation

OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library.

OpenCV Features​

  • High Performance

    Optimized with C++ under the hood, it provides interfaces for Python, Java, and other languages, balancing speed and usability. Supports GPU acceleration (CUDA, OpenCL).

  • Cross-Platform

    Supports Windows, Linux, macOS, Android, and iOS, and can run on various hardware architectures including x86 and ARM.

  • Multi-language Support

    Offers interfaces for C++, Python, Java, and more, catering to different development needs. Compatible with deep learning frameworks like TensorFlow and PyTorch.

  • Rich Functionality

    OpenCV provides a wide range of computer vision algorithms, including image processing, feature detection, object detection, and machine learning.

Installing OpenCV​

This guide covers two different methods to install OpenCV: binary installation and source code compilation. Choose the one that best suits your needs.

Installation MethodAdvantagesDisadvantagesBest For
Binary Installation- Quick and easy installation
- No need to compile from source
- Easy to maintain and upgrade		- May lack some features
- Less customizable		Beginners, daily development, Python users
Source Installation- Customizable compilation parameters and modules
- Access to latest/specific versions
- Supports multiple languages		- Complex process
- Requires build environment
- Time-consuming compilation		Advanced users, C++ developers, special requirements

Binary Installation​

You can install the Python version of OpenCV using pip, or the C++ version using apt.

radxa@device$
pip3 install opencv-python opencv-contrib-python
  • Verify OpenCV Installation

Open a terminal and enter the Python interactive mode by typing python3.

radxa@device$
python3

Once in the Python interactive mode, enter the following commands to verify OpenCV installation:

radxa@device$
import cv2
print(cv2.__version__)

If the OpenCV version number is displayed, the installation was successful.

Source Installation​

This method involves compiling OpenCV from source.

Install Build Dependencies​

radxa@device$
sudo apt update
sudo apt install cmake gcc g++ python3-dev python3-numpy libavcodec-dev libavformat-dev libswscale-dev libgstreamer-plugins-base1.0-dev libgstreamer1.0-dev libgtk-3-dev -y

Install Optional Dependencies​

radxa@device$
sudo apt install libpng-dev libjpeg-dev libopenexr-dev libtiff-dev libwebp-dev -y

Download OpenCV Source Code​

Use git to download the OpenCV source code.

radxa@device$
sudo apt install git -y
git clone https://github.com/opencv/opencv.git

Compile OpenCV​

Navigate to the OpenCV source directory and run the following commands to compile OpenCV:

radxa@device$
cd opencv
mkdir build
cd build
cmake ../
make -j4
sudo make install

Verify OpenCV Installation​

Open a terminal and enter the Python interactive mode by typing python3.

radxa@device$
python3

Once in the Python interactive mode, enter the following commands to verify OpenCV installation:

radxa@device$
import cv2
print(cv2.__version__)

If the OpenCV version number is displayed, the installation was successful.