pyidi 0.30.1

Python Image Displacement Identification.

pyidi

Image-based Displacement Identification (IDI) implementation in python.

See the documentation for pyIDI.

Use Napari UI for quick displacement identification:

BASIC USAGE:

Create an instance:

video = pyidi.pyIDI(input_file='video.cih')

The pyIDI method works with various formats: .cih, .cihx, .png, .avi etc. Additionally, it can also work with numpy.ndarray as input. If an array is passed, it must have a shape of: (n time points, image height, image width).

Set the points where displacements will be determined:

p = np.array([[0, 1], [1, 1], [2, 1]]) # example of points
video.set_points(points=p)

Or use point selection UI to set individual points or grid inside selected area. For more information about UI see documentation. Launch viewer with:

video.gui()

The method of identification has to be specified:

video.set_method(method='sof', **method_kwargs)

After points are set, displacements can be calculated (using method, set in set_method):

displacements = video.get_displacements()

Multiprocessing can also be used by passing the processes argument:

displacements = video.get_displacements(processes=4)

DEVELOPER GUIDELINES:

• Add _name_of_method.py with class that inherits after IDIMethods
• This class must have methods:
  • calculate_displacements with attribute displacements
  • get_points (static method - sets attribute video.points)
• In pyIDI add a new method of identification in avaliable_methods dictionary.

Citing

If you are using the pyIDI package for your research, consider citing our articles:

• Čufar, K., Slavič, J., & Boltežar, M. (2024). Mode-shape magnification in high-speed camera measurements. Mechanical Systems and Signal Processing, 213, 111336. https://doi.org/10.1016/J.YMSSP.2024.111336
• Zaletelj, K., Gorjup, D., Slavič, J., & Boltežar, M. (2023). Multi-level curvature-based parametrization and model updating using a 3D full-field response. Mechanical Systems and Signal Processing, 187, 109927. https://doi.org/10.1016/j.ymssp.2022.109927
• Zaletelj, K., Slavič, J., & Boltežar, M. (2022). Full-field DIC-based model updating for localized parameter identification. Mechanical Systems and Signal Processing, 164. https://doi.org/10.1016/j.ymssp.2021.108287
• Gorjup, D., Slavič, J., & Boltežar, M. (2019). Frequency domain triangulation for full-field 3D operating-deflection-shape identification. Mechanical Systems and Signal Processing, 133. https://doi.org/10.1016/j.ymssp.2019.106287