AGL Anonymizer

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.

Features of the pipeline

• Text Detection and Anonymization: Leverages advanced OCR techniques to detect and anonymize text within images, safeguarding sensitive information.
• Blurring Functionality: Includes customizable blurring options to obscure specific areas of an image, enhancing privacy.
• Image Saving: Efficiently saves processed images in the desired format while maintaining high-quality output.
• Extensive Format Support: Capable of handling various image and document formats for diverse applications.
• Pdf,

Installation

To get started with AGL Anonymizer, follow these steps:

1. Clone the Repository:

   git clone https://github.com/wg-lux/agl_anonymizer.git
   cd agl_anonymizer
   

2. Set Up the Development Environment:

   nix develop
   

3. Install Dependencies: Ensure you have all required dependencies installed. Refer to pypoetry.toml for a list of dependencies.

4. Download the Text Detection Model: Download a text detection model, such as frozen_east_text_detection.pb, and place it in the appropriate directory.

Usage

To use the AGL Anonymizer API, follow these steps:

1. Prepare Your Images: Place the images you want to process in a designated folder.

2. Configure Settings: Adjust settings in the configuration file (if applicable) to suit your anonymizing and blurring needs.

3. Run the Django Server:

   python manage.py runserver
   

4. 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
   

API Endpoints

• /process/: Endpoint to upload images and receive anonymized results.

Modules

AGL Anonymizer API comprises several key modules:

• OCR Module: Detects and extracts text from images.
• Anonymizer Module: Applies anonymization techniques to identified sensitive text regions.
• Blur Module: Provides functions to blur specific areas in the image.
• Save Module: Handles the saving of processed images in a chosen format.

Models

UploadedFile

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