Skip to main content

crack detection for composite materials

Reason this release was yanked:

Missing prerequisites

Project description

CrackDect

Expandable crack detection for composite materials.

alt text

This package provides an automated crack detection for tunneling off axis cracks in glass fiber reinforced materials. It relies on image processing and works with transilluminated white light images (TWLI). The basis of the crack detection method was first published by Glud et al. [1]. This implementation is aimed to provide a modular "batteries included" package for this method and extensions of it as well as image preprocessing functions.

Quick start

To install CrackDect, check at first the prerequisites of your python installation. Upon meeting all the criteria, the package can be installed with pip, or you can clone or download the repo. If the installed python version or certain necessary packages are not compatible we recommend the use of virtual environments by virtualenv or Conda.

Installation:

pip install crackdect

Documentation:

https://crackdect.readthedocs.io/en/latest/

Prerequisites

This package is written and tested in Python 3.8. The following packages must be installed.

Motivation

Most algorithms and methods for scientific research are implemented as in-house code and not accessible for other researchers. Code rarely gets published and implementation details are often not included in papers presenting the results of these algorithms. Our motivation is to provide transparent and modular code with high level functions for crack detection in composite materials and the framework to efficiently apply it to experimental evaluations.

Contributing

Clone the repository and add changes to it. Test the changes and make a pull request.

Authors

  • Matthias Drvoderic

License

This project is licensed under the MIT License.

[1] J.A. Glud, J.M. Dulieu-Barton, O.T. Thomsen, L.C.T. Overgaard Automated counting of off-axis tunnelling cracks using digital image processing Compos. Sci. Technol., 125 (2016), pp. 80-89

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

crackdect-0.1.tar.gz (22.3 kB view details)

Uploaded Source

Built Distribution

crackdect-0.1-py3-none-any.whl (23.4 kB view details)

Uploaded Python 3

File details

Details for the file crackdect-0.1.tar.gz.

File metadata

  • Download URL: crackdect-0.1.tar.gz
  • Upload date:
  • Size: 22.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.10.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.8.8

File hashes

Hashes for crackdect-0.1.tar.gz
Algorithm Hash digest
SHA256 ca3f4a0efb22e0020c372d8fe02ab111ecd5b33ad0869e52a5df53a947c5c657
MD5 6d701ed1275060d7c0a7b0ef719c03d0
BLAKE2b-256 004169addb086767136a4aec48f661ec4d66d00978f99dfeb35c77ac0b4b28a2

See more details on using hashes here.

File details

Details for the file crackdect-0.1-py3-none-any.whl.

File metadata

  • Download URL: crackdect-0.1-py3-none-any.whl
  • Upload date:
  • Size: 23.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.10.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.8.8

File hashes

Hashes for crackdect-0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 b6d5bee9cee94712e97a3046da50a79f11ac7b073b12a87d77440ebe733f8255
MD5 1fba82f7cac10648766260f53b3516bd
BLAKE2b-256 1814c7b32f88e006c5d49fd0f699ccf95544385ea5db0a708fc8e169209a87d6

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page