Feature Detection

Wagtail has the ability to automatically detect faces and features inside your images and crop the images to those features.

Feature detection uses OpenCV, the Open Source Computer Vision Library, to detect faces/features in an image when the image is uploaded. The detected features are stored internally as a focal point in the focal_point_{x, y, width, height} fields on the Image model. These fields are used by the fill image filter when an image is rendered in a template to crop the image.

Installation

Three components are required to get this working with Wagtail:

  • OpenCV itself
  • various system-level components that OpenCV relies on
  • a Python interface to OpenCV, exposed as cv2

Installation options

There is more than one way to install these components, but in each case you will need to test that both OpenCV itself and the Python interface have been correctly installed.

Install opencv-python

opencv-python is available on PyPI. It includes a Python interface to OpenCV, as well as the statically-built OpenCV binaries themselves.

To install:

$ pip install opencv-python

Depending on what else is installed on your system, this may be all that is required. On lighter-weight Linux systems, you may need to identify and install missing system libraries (for example, a slim version of Debian Stretch requires libsm6 libxrender1 libxext6 to be installed with apt).

Install a system-level package

A system-level package can take care of all of the required components. Check what is available for your operating system. For example, python-opencv is available for Debian; it installs OpenCV itself, and sets up Python bindings.

However, it may make incorrect assumptions about how you’re using Python (for example, which version you’re using) - test as described below.

Testing the installation

Test the installation:

python3
>>> import cv2

An error such as:

ImportError: libSM.so.6: cannot open shared object file: No such file or directory

indicates that a required system library (in this case libsm6) has not been installed.

On the other hand,

ModuleNotFoundError: No module named 'cv2'

means that the Python components have not been set up correctly in your Python environment.

If you don’t get an import error, installation has probably been successful.

Switching on feature detection in Wagtail

Once OpenCV is installed, you need to set the WAGTAILIMAGES_FEATURE_DETECTION_ENABLED setting to True:

# settings.py

WAGTAILIMAGES_FEATURE_DETECTION_ENABLED = True

Manually running feature detection

Feature detection runs when new images are uploaded in to Wagtail. If you already have images in your Wagtail site and would like to run feature detection on them, you will have to run it manually.

You can manually run feature detection on all images by running the following code in the Python shell:

from wagtail.images.models import Image

for image in Image.objects.all():
    if not image.has_focal_point():
        image.set_focal_point(image.get_suggested_focal_point())
        image.save()