11bhanuprakash/Master_thesis_DIC ? reverse-engineered prompt

Build me a Python tool for automated digital image correlation on image sequences from microwave drying experiments. I want to drop in a folder of images plus a JSON config, then run one main script that handles the full workflow end to end. It should detect the circular fiducial markers, align the images, automatically find the circular region of interest, improve contrast when needed, compute full field displacement, and measure shrinkage and internal deformation over time.

Please save the results in clean CSV files and also include post processing that makes useful plots and summary outputs. I also want a simple interactive slider view so I can scrub through the sequence and see how the corner markers or tracked points move on the reference image.

Keep it built on top of the existing μDIC approach rather than rewriting everything. Make the setup and usage clear, with example configs and a straightforward command line entry point. If anything is unclear, check the μDIC docs and use the documentation folder in the repo.