(Python Rewritten Digital Image Correlation)
Digital Image Correlation in Python 3. Using spline interpolation and Newton-Raphson convergence. All contributors give full credit to Dr Ghulam Mubashar Hassan for providing the original matlab code on which this program is based.
To setup & install dependencies we will create a virtual environment and install from requirements.txt.
First run
python3 -m venv venv
to create a virtual environment, then
python3 -m pip install -r requirements.txt
to install the necessary packages into the virtual environment.
From the predic package, import the class DIC_NR.
In code you create it, then supply it with the parameters in set_parameters to calculate deformation from.
These parameters are the reference image, deformed image, subset size, and initial guess.
After that, the method calculate will return the results as a numpy array.
For example:
import predic as dm
dic = dm.DIC_NR()
dic.set_parameters("ref_image.bmp", "def_image.bmp", 11, [0, 0])
results = dic.calculate()
print(results)A helpful script is included in the root directory of this repo named measure_deformation.py.
To run it with default settings, mark it as executable and then use ./measure_deformation.py ref_image.bmp def_image.bmp.
For an explanation of all the parameters run ./measure_deformation.py -h.
Run python test to run the full test suite.
For testing a specific file you can use python test Test_C_First_Order or python test Test_DIC_NR.