UtilityKit

500+ fast, free tools. Most run in your browser only; Image & PDF tools upload files to the backend when you run them.

Face Blur — Auto Detect & Blur Faces

Automatically detect and blur faces in images using AI. Add manual regions. Download anonymized PNG.

About Face Blur — Auto Detect & Blur Faces

Face Blur Auto detects and blurs faces in images entirely in your browser using the @vladmandic/face-api TinyFaceDetector model (~2 MB). Click 'Detect Faces' to auto-find all faces and apply Gaussian or pixelate blur. A badge shows how many faces were detected. Adjust the blur intensity (5–50 px) and switch between smooth Gaussian blur or pixelation for a CCTV-style effect. You can also draw manual blur regions by clicking and dragging on the canvas — useful for obscuring logos, license plates, or other identifying details. Download the final image as a lossless PNG.

Why use Face Blur — Auto Detect & Blur Faces

AI face detection runs

AI face detection runs entirely in-browser — no image leaves your device.

Tiny model (~2 MB)

Tiny model (~2 MB) loads in seconds on any connection.

Manual region drawing covers logos

Manual region drawing covers logos, plates, and other non-face content.

Choose between smooth Gaussian

Choose between smooth Gaussian blur or high-contrast pixelation.

Free and instant with

Free and instant with no signup or watermarks.

AI face detection runs

AI face detection runs entirely in-browser via WebGL — no image leaves your device, ideal for GDPR/HIPAA workflows.

How to use Face Blur — Auto Detect & Blur Faces

  1. Upload a JPG, PNG, or WebP image containing faces.
  2. Click 'Detect Faces'. The AI model (~2 MB) loads on first use.
  3. Detected faces are blurred automatically and a count badge appears.
  4. Adjust the blur intensity slider and switch blur style (Gaussian or Pixelate) to update live.
  5. Click and drag on the image canvas to add manual blur regions for other sensitive areas.
  6. Click 'Download PNG' to save the anonymized image.
  7. Upload a JPG, PNG, or WebP image containing one or more faces.

When to use Face Blur — Auto Detect & Blur Faces

  • Anonymizing faces before sharing photos on social media or in publications.
  • Preparing images for GDPR-compliant use in marketing or research.
  • Blurring background bystanders in event or street photography.
  • Redacting identifying features from screenshots or screen recordings.
  • Anonymising faces before sharing photos on social media, blogs, or in press articles.
  • Preparing images for GDPR-compliant publication in marketing or research case studies.

Examples

Group photo redaction

Input: JPG of an office team photo with 12 visible faces, 4032 × 3024 px

Output: Anonymised PNG with 12 detected faces blurred plus 2 manual regions over name badges; face count badge reads '12'.

Street scene

Input: PNG screenshot of a busy crosswalk taken from a security camera

Output: PNG with 4 detected faces pixelated plus 2 manual regions over visible licence plates; suitable for an insurance claim.

Conference candid

Input: JPG photo of a speaker on stage with audience faces in the foreground

Output: PNG with the speaker untouched (manual exclusion not needed because the audience faces are the only ones detected behind a manual focus region).

Tips

  • Run detection first, then add manual regions for anything missed — the AI handles 95% of front-facing faces but profiles or partially occluded faces sometimes slip through.
  • Use Pixelate for journalistic redaction (it cannot be reversed by deblurring algorithms) and Gaussian for aesthetic anonymisation in marketing photos.
  • Crank the blur radius up to 30+ px for small faces in group photos — small Gaussian radii on tiny faces can leave recognisable structure.
  • If a face is detected with a tight bounding box, increase the radius or draw a slightly larger manual region around it to cover ears, jawline, and stray hair.
  • Always download the PNG before closing the tab — there is no auto-save and your edits are kept only in browser memory.
  • When publishing legally-sensitive redactions, prefer pixelation; certain Gaussian-blurred faces have been deanonymised by published research, while pixelation with a large block size resists those attacks.

Frequently Asked Questions

Does it upload my image?▾
No. The face detection model and blur both run in your browser via WebGL. Nothing is sent to any server.
How accurate is the face detection?▾
The TinyFaceDetector handles most front-facing portraits reliably. Extreme angles, heavy occlusion, or very small faces may be missed — use the manual drawing tool to add those regions.
What is the difference between Gaussian and Pixelate blur?▾
Gaussian applies a smooth blurring effect. Pixelate replaces the region with large blocks, like a CCTV-style censor bar.
Can I blur areas that are not faces?▾
Yes. Click and drag anywhere on the canvas to draw a manual blur region — useful for license plates, names, or logos.
What output format does it produce?▾
A lossless PNG regardless of the input format.
Is the model size really only 2 MB?▾
The TinyFaceDetector model from @vladmandic/face-api is approximately 1–2 MB, much smaller than full ResNet-based detectors.

Explore the category

Image Rotate Tool Rotate images 90° CW, 90° CCW, or 180° in your browser. Canvas-based, instant PNG download. Image Grayscale, Sepia & Filter Tool Apply grayscale, sepia, invert, blur, or sharpen filters to any image in your browser. Preview and download as PNG. Simple Collage Grid Maker Combine multiple images into a grid collage in your browser. Pick a layout, set padding and background, download as PNG. Image Border & Frame Adder Add a custom border with color and rounded corners to any image. Browser-only, download as PNG. Image Batch Rename & Download Rename multiple images using a pattern with {n} and {name} placeholders, preview new names, and download as ZIP. Image to SVG Tracer Convert PNG, JPG, or GIF images to scalable SVG vectors in your browser. Adjust colors, smoothness, and download.

Glossary

TinyFaceDetector
A compact (~2 MB) face-detection neural network designed for real-time inference in browsers; trades a small amount of accuracy for very fast load and run times.
ONNX
Open Neural Network Exchange — a portable model format for shipping trained networks; face-api uses TensorFlow.js and a similar tensor format internally.
WebGL
A browser graphics API that exposes GPU shaders to JavaScript; face-api uses it to run the detection network on your GPU for low-latency inference.
Gaussian blur
A smoothing filter that averages each pixel with its neighbours weighted by a Gaussian curve; produces a soft, natural-looking blur.
Pixelation (mosaic)
A blur technique that replaces a region with large coloured blocks; preferred for journalistic redaction because it resists deblurring attacks better than Gaussian.
Bounding box
The rectangle returned by the detector that encloses each detected face; the blur is applied within this box plus a margin.
IndexedDB
A browser-based persistent database used to cache the face detection model so the 2 MB download only happens once per browser profile.