Worm length#

In this project, the length of california blackworms (Lumbriculus variegatus) is measured in 6 well plates, which are detected automatically with the Hough Transform algorithm in detect_mask.


Get started#

  1. Read the jupyter notebooks for this project

  2. Download the materials (see downloads section below)

  3. Run the project yourself (see general instructions)


Body length is a commonly measured trait. However, live animals are typically not well behaved in front of camera: typically the body is not aligned straight, which makes length measure difficult and sometimes time consuming. Some computer vision can help here, such as skeletonization for an acurate semi automatic approach, and polyline drawing for a less acurate, manual aproach. phenopype’s detect_mask can automatically detect geometric objects using Hough transformation. It can take a while to fine-tune the right parameters for the circle detection. For this particular project, the below configuration for detect_mask(included in the template) proved to be useful for the 6-well plates in the images:

- detect_mask:
    ANNOTATION: {type: mask, id: a, edit: overwrite}
    shape: circle
    circle_args: {max_radius: 300, min_radius: 220, param2: 90, param1: 100, min_dist: 400}
    resize: 0.5

Jupyter notebooks#

Jupyter notebook

Read a static html render of a jupyter notebook


Project materials

Download data, scripts, and template