Contents

presidio-image-redactor 0.0.53

0

Presidio image redactor package

Presidio image redactor package

Stars: 3710, Watchers: 3710, Forks: 565, Open Issues: 81

The microsoft/presidio repo was created 6 years ago and the last code push was 3 days ago.
The project is very popular with an impressive 3710 github stars!

How to Install presidio-image-redactor

You can install presidio-image-redactor using pip

pip install presidio-image-redactor

or add it to a project with poetry

poetry add presidio-image-redactor

Package Details

Author
Presidio
License
MIT
Homepage
None
PyPi:
https://pypi.org/project/presidio-image-redactor/
GitHub Repo:
https://github.com/Microsoft/presidio

Classifiers

No  presidio-image-redactor  pypi packages just yet.

Errors

A list of common presidio-image-redactor errors.

Code Examples

Here are some presidio-image-redactor code examples and snippets.

GitHub Issues

The presidio-image-redactor package has 81 open issues on GitHub

  • Analyzer is recognizing 'today'/'a moment' as date or date_time, how to rectify to precise date_times only?
  • 'RecognizerResult' object has no attribute 'recognition_metadata'
  • Use base64 encoded key
  • Not be able to use a random key in encrypt and decrypt operators
  • Fix type mismatch in check_label_groups parameter in SpacyRecognizer
  • How to filter Entities in ImageRedactorEngine
  • Bump certifi from 2023.5.7 to 2023.7.22 in /presidio-cli
  • Bump certifi from 2023.5.7 to 2023.7.22 in /presidio-image-redactor
  • Bump certifi from 2023.5.7 to 2023.7.22 in /presidio-analyzer
  • Presidio Tabular Referential integrity
  • Presidio Tabular
  • Use group from matched pattern (PatternRecognizer)
  • Deny List Recognizer
  • DICOM redactor improvement: Enable selection of redact approach
  • Presidio Max Length Change

See more issues on GitHub

Related Packages & Articles

auto-gptq 0.7.1

An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.

spark-nlp 5.5.0

John Snow Labs Spark NLP is a natural language processing library built on top of Apache Spark ML. It provides simple, performant & accurate NLP annotations for machine learning pipelines, that scale easily in a distributed environment.