Anonymize your data
Project description
privapy
Anonymize your data
Documentation
Visit Read the Docs for the full documentation, including overviews and several examples.
Installation
pip install privapy
Disclaimer
This package provides no guarantee of anonymity. It is the user's responsibility to ensure that the data is properly anonymized. The authors of this package are not responsible for any results or misuse of this package.
Usage
text
from privapy.text import TextCleaner
text = "I live in New York and work at Google. My email is john@google.com"
cleaner = TextCleaner(steps="all")
cleaned_text = cleaner.clean(text)
# 'I live in <<ENT>> and work at <<ENT>. My email is <<EMAIL>>'
image
from privapy.image import ImageCleaner
from PIL import Image
cleaner = ImageCleaner()
img = Image.open("image.jpg")
cleaned_image = cleaner.clean(img)
input image (img
):
output image (cleaned_image
):
Coming in future releases
- text
- Add more cleaning methods
- Add Spacy integration
- image
- Add more cleaning methods
- blackout
- pixelate
- Add more detection methods
- face detection
- dlib
- mediapipe
- Add more cleaning methods
Project details
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Source Distribution
privapy-0.0.4.tar.gz
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privapy-0.0.4-py3-none-any.whl
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