This post will use the OpenCV Python library to apply an oil painting effect to an image.

Let's create the oil-paint-effect-with-open-cv-python directory and install Pillow.

# Make the `oil-paint-effect-with-open-cv-python` directory
$ mkdir oil-paint-effect-with-open-cv-python
$ cd oil-paint-effect-with-open-cv-python
$ touch main.py

# Init the virtual environment
$ pipenv --three
$ pipenv install opencv-python opencv-contrib-python


# if you have issues with a hanging lockfile, try add the --skip-lock option
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At this stage, you will need to add an image to the root of your directory. In my case, I will add base_img.jpg to the directory (which will be an image from Unsplash).

We are now ready to start coding!

This section simply loads the image in var base_img (assuming you are following the directory structure where the notebook is in the docs folder).

import cv2
img = cv2.imread('./base_img.jpg')
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Once that is complete, we can apply the oil paiting effect with one liner of code:

res = cv2.xphoto.oilPainting(img, 7, 1)
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We can now compare by displaying the images:

cv2.imshow("original", img)
cv2.imshow("res", res)
cv2.waitKey(0)
cv2.destroyAllWindows()
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This will display the images in a window.

The original image:

Original

After applying the effect:

After effect

When you are finished with viewing, hit escape to exit.

Today's post demonstrated how to use the OpenCV package to programmatically apply an oil painting effect to an image.

Photo credit: dancristianp