Skip to main content

A python library for performing surgical skills evaluation

Project description

Logo

GitHub Actions CI status Test coverage Documentation Status The SciKit-Surgery paper https://img.shields.io/badge/Contributor%20Covenant-2.1-4baaaa.svg Follow scikit_surgery on twitter

Author: Stephen Thompson

scikit-surgery-evaluation provides an application to evaluate surgical skills. You can provide a set of unstructured grids representing a set of locations that the user is then expected to target using a tracked pointer, utilising a SciKit-Surgery tracking library (scikit-surgeryarucotracker, or scikit-surgerynditracker). You can specify paths for the user to follow, or let the system select target meshes automatically.

scikit-surgery-evaluation is part of the SciKit-Surgery software project, developed at the Wellcome EPSRC Centre for Interventional and Surgical Sciences, part of University College London (UCL).

scikit-surgery-evaluation supports Python 3.X.

python sksurgeryeval.py -c configuration.json

Developing

Cloning

You can clone the repository using the following command:

git clone https://github.com/SciKit-Surgery/scikit-surgery-evaluation

Running tests

Pytest is used for running unit tests:

pip install pytest
python -m pytest

Linting

This code conforms to the PEP8 standard. Pylint can be used to analyse the code:

pip install pylint
pylint --rcfile=tests/pylintrc sksurgeryeval

Installing

You can pip install directly from the repository as follows:

pip install git+https://github.com/SciKit-Surgery/scikit-surgery-evaluation

Contributing

Please see the contributing guidelines.

Acknowledgements

Supported by Wellcome and EPSRC.

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

scikit-surgery-evaluation-0.0.4.tar.gz (27.8 kB view details)

Uploaded Source

Built Distribution

scikit_surgery_evaluation-0.0.4-py2.py3-none-any.whl (19.2 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file scikit-surgery-evaluation-0.0.4.tar.gz.

File metadata

  • Download URL: scikit-surgery-evaluation-0.0.4.tar.gz
  • Upload date:
  • Size: 27.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.10

File hashes

Hashes for scikit-surgery-evaluation-0.0.4.tar.gz
Algorithm Hash digest
SHA256 2bef5e91ef7052dbf045f517ae6f615e378e9e3351f6f36e8bec19d6b8809aff
MD5 1f8c4e07b537bb126f9765206cdbce94
BLAKE2b-256 e8400382bd2721c19eb90957f5c3d1358c9f8ef11099e8b4d6d7ae750d294188

See more details on using hashes here.

File details

Details for the file scikit_surgery_evaluation-0.0.4-py2.py3-none-any.whl.

File metadata

  • Download URL: scikit_surgery_evaluation-0.0.4-py2.py3-none-any.whl
  • Upload date:
  • Size: 19.2 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.10

File hashes

Hashes for scikit_surgery_evaluation-0.0.4-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 1df7f170b46964505e38058099a643992c2534425df6162626172706429f85be
MD5 b8bc1d2ea6aee1846e9acc99be525596
BLAKE2b-256 c1f7403f54bb733d78b4e9bf52a464bb2a38b0663d3e8c676027f1487b98932a

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