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This repository contains the codes for computing crack kinematics using a binary mask that represents a segmented crack. The methodoly hereby implementes was presented in the paper "Determing crack kinematics from imaged crack patterns" by Pantoja-Rosero et., al.

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Crack Kinematics (tested on ubuntu 18.04 lts)

This repository contains the codes for computing crack kinematics using a binary mask that represents a segmented crack. The methodoly hereby implementes was presented in the paper "Determing crack kinematics from imaged crack patterns" by Pantoja-Rosero et., al.

How to use it?

1. Clone repository

Clone repository in your local machine. All codes related with method are inside the src directory.

2. Download data

Download data file from Data. Extract the folder data/ and place it inside the repository folder

2a. Repository directory

The repository directory should look as:

dt_smw
└───src
└───data
└───results

3. Environment

Create a conda environment and install python packages. At the terminal in the repository location.

conda create -n crack_kinematics python=3.8

conda activate crack_kinematics

pip install -r requirements.txt

4. Using method

The main functions of the methodology to compute the crack kinematics of crack patterns using binary mask images are placed in src/least_square_crack_kinematics.py. Test them with the examples provided as follows:

python example/example_kinematics_pattern.py python example/example_kinematics_patch.py

5. Using your own data

The methodology requires as input a binary mask that represents a segmented crack. Create a folder containing the image to be analysed inside the data folder and run the algorithms as shown in the example files src/example_kinematics_pattern.py or src/example_kinematics_patch.py.

6. Results

The results will be saved inside results folder with the same name of the folder containing the input image. This contain a json file with all the displacements computed for the crack skeleton. Further, figures that represent the kinematics are output in the same folder.

7. Paper experiments

The scripts used to run the experiments presented in the paper can be found inside the folder paper_examples

8. Citation

We kindly ask you to cite us if you use this project, dataset or article as reference.

Paper:

@article{Pantoja-Rosero2020c,
title = {Determining crack kinematics from imaged crack patterns},
journal = {Construction and Building Materials},
volume = {343},
pages = {128054},
year = {2022},
issn = {0950-0618},
doi = {https://doi.org/10.1016/j.conbuildmat.2022.128054},
url = {https://www.sciencedirect.com/science/article/pii/S0950061822017202},
author = {B.G. Pantoja-Rosero and K.R.M. {dos Santos} and R. Achanta and A. Rezaie and K. Beyer},
}

Dataset:

@dataset{Pantoja-Rosero2020c-ds,
  author       = {Pantoja-Rosero Bryan German and
                  Dos Santos Ketson and
                  Achanta Radhakrishna and
                  Rezaie Amir and
                  Beyer Katrin},
  title        = {{Dataset for determining crack kinematics from 
                   imaged crack patterns}},
  month        = jun,
  year         = 2022,
  publisher    = {Zenodo},
  version      = {v0.0},
  doi          = {10.5281/zenodo.6632071},
  url          = {https://doi.org/10.5281/zenodo.6632071}
}

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This repository contains the codes for computing crack kinematics using a binary mask that represents a segmented crack. The methodoly hereby implementes was presented in the paper "Determing crack kinematics from imaged crack patterns" by Pantoja-Rosero et., al.

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