These are a few exercises implemented as homeworks for a computer vision class using OpenCV 3 in Python 3. The goal for the exercises proposed was to introduce to using the most known and used open library for computer vision that there is. OpenCV is available for many languages and has a huge impact and usability for developing new projects. Yet, these homeworks should ideally give enough support for creating new applications as a class result.
Following there are some needs and helps to make it work. I list below Linux as a prerequisite because installing OpenCV in windows is not trivial and should be avoided if possible.
- Linux
- Python 3 (3.7 used)
- OpenCV 3
I suggest creating a virtualenv inside the repository folder to installing all the dependencies.
pip install virtualenv
virtualenv envname
source envname/bin/activate
Now with the env created and activated, install Python and OpenCV inside it.
sudo apt-get install python3.7
sudo apt install python3-opencv
To deactivate the virtualenv after use simply type deactivate.
Once you have the env activated and is inside the repository folder, simply execute the python files.
python labeling.py
The explanation of each file is discussed on my medium page in a 5 part series. There I go through the theory behind the solutions and also analyse the code line by line.