Observed since 21 Oct, 09:13 UTC
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This package is made to censor sensitive data in images and extract the contents. NER is planned for the future
AGL Anonymizer is a Django-based API that interacts with the AGL Anonymizer Pipeline to provide comprehensive image processing capabilities, specifically for anonymizing sensitive information using common German names, blurring, and OCR (Optical Character Recognition). This API is designed to facilitate the seamless integration of anonymization functionalities into various applications, ensuring privacy and compliance with data protection regulations.
To get started with AGL Anonymizer, follow these steps:
Clone the Repository:
git clone https://github.com/wg-lux/agl_anonymizer.git
cd agl_anonymizer
Set Up the Development Environment:
nix develop
Install Dependencies:
Ensure you have all required dependencies installed. Refer to pypoetry.toml for a list of dependencies.
Download the Text Detection Model:
Download a text detection model, such as frozen_east_text_detection.pb, and place it in the appropriate directory.
To use the AGL Anonymizer API, follow these steps:
Prepare Your Images: Place the images you want to process in a designated folder.
Configure Settings: Adjust settings in the configuration file (if applicable) to suit your anonymizing and blurring needs.
Run the Django Server:
python manage.py runserver
Make API Requests: Decide first, if validation of the anonymization is necessary. (only available with a running instance of agl-validator) If so, the validation flag needs to be set to true inside of the request.
Use an API client like Postman, cURL, or the requests library in Python to interact with the AGL Anonymizer API. Example request using the requests library:
import requests
import os
# Get the directory of the current script
base_dir = os.path.dirname(os.path.abspath(__file__))
# Define the path to the image file located in the 'requests_agl_anonymizer' folder
image_path = os.path.join(base_dir, 'frame_0.jpg')
# Ensure the file exists
if not os.path.exists(image_path):
raise FileNotFoundError(f"No such file or directory: '{image_path}'")
# Define the URL of the Django API endpoint
url = 'http://127.0.0.1:8000/process/'
# Open the file in binary mode and send it as part of the multipart form-data payload
with open(image_path, 'rb') as image_file:
files = {
'file': image_file,
}
data = {
'title': 'Example Image',
}
response = requests.post(url, files=files, data=data)
# Print the response from the server
print(response.status_code)
print(response.json()) # Assuming the server returns a JSON response
AGL Anonymizer API comprises several key modules:
Represents an uploaded file with fields for the original file, upload date, and an optional description.
from django.db import models
from django.utils import timezone
class UploadedFile(models.Model):
original_file = models.FileField(upload_to='uploads/original/')
upload_date = models.DateTimeField(default=timezone.now)
description = models.TextField(blank=True, null=True)
def __str__(self):
return self.original_file.name
Download counts and popularity will appear here as the collector receives them.
| Version | Published | Direct dependencies | Open version |
|---|---|---|---|
| 0.1.1 | 6 Sept 2024 | 18 |
This describes our collected data; it is not a security assessment.
Observed since 21 Oct, 09:13 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
package:aed2e49bc63255363a15019f5dbd8972496dec6528b74a152c0d44312d85f5d8