---
id: presidio-image-redactor
version: "0.0.60"
license: MIT
license_treatment: permissive
maintenance: active
---

# presidio-image-redactor — Presidio image redactor package

License: permissive · Maintenance: active · Downloads: 168.3K/mo

## What it is and what it does

Presidio Image Redactor is a Python module that finds and masks PII text embedded in images and DICOM medical files. It combines OCR via pytesseract with named-entity recognition via spacy and presidio-analyzer to locate sensitive text, then covers those regions with a solid color or pattern of your choice.

The package handles both standard image formats and DICOM medical imaging files. For DICOM, it redacts only pixel-level burn-in text and does not modify metadata; the documentation explicitly recommends using a separate tool for metadata scrubbing. It supports batch processing from directories and can optionally return bounding boxes of redacted regions. The module runs as a Python library or as a Docker service with an HTTP API.

Use it for:

- Anonymize photographs or scanned documents before sharing them in research or compliance workflows.
- Remove patient names and medical record numbers from DICOM images before publishing or archiving.
- Batch-redact burn-in text from medical imaging studies to prepare datasets for machine learning training.
- Build a privacy-preserving image pipeline in a web service using the HTTP API or Docker deployment.
- Detect and mask PII in user-uploaded images to enforce data minimization policies.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Detects and redacts personally identifiable information (PII) text in images and DICOM medical files using OCR and named-entity recognition.

Yes, if you need to redact PII text from images or DICOM files. The package is actively maintained, has no known vulnerabilities, uses a permissive MIT license, and integrates with standard image libraries. The main gotcha is the Tesseract OCR system dependency—plan for that installation before deploying. Not suitable if you need metadata-level DICOM anonymization without a separate tool.

## Install

pip install presidio-image-redactor
uv add presidio-image-redactor
poetry add presidio-image-redactor

## Installing presidio-image-redactor

Before you install: Low friction install with a pure-Python wheel. Active maintenance (last commit 2026-08-11) and no known vulnerabilities. Requires Tesseract OCR as a system dependency; documentation specifies v5.2.0 for best results.

License in practice: MIT license permits commercial and private use with minimal restrictions—suitable for most production deployments.

Quickstart:

pip install presidio-image-redactor
python -m spacy download en_core_web_lg

from presidio_image_redactor import ImageRedactorEngine
from pillow import Image

image = Image.open("image.png")
engine = ImageRedactorEngine()
redacted = engine.redact(image, (255, 192, 203))
redacted.save("redacted.png")

Tesseract OCR must be installed on your system (not via pip). Documentation recommends v5.2.0. The spacy model en_core_web_lg must be downloaded after package installation.

Verify before relying:

- Actual redaction accuracy and false-positive rates for different image types and quality levels.
- Performance characteristics (processing time per image, memory usage) at scale.
- Whether DICOM metadata scrubbing is handled by this package or requires a separate tool as the docs suggest.

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 168.3K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

redact pii from images, ocr text detection and removal, dicom image anonymization, burn-in text redaction, image privacy masking, medical image de-identification, pii detection in photos, pii-redaction, ocr, dicom

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