Face Blur

The tool uses a TinyFaceDetector neural network to locate all faces in the uploaded photo. Once detected, each face region is highlighted with a bounding box and selected for blurring by default. You choose between two blur modes — pixelation breaks the face area into large color blocks, while Gaussian blur smoothly obscures facial features. The intensity slider controls how aggressively the face is hidden. All processing happens on the HTML5 Canvas API entirely in your browser. For counting faces without blurring, use the Face Counter tool.

GDPR and similar privacy laws require consent before publishing identifiable photos of individuals. Street photographers, journalists, and event organizers blur bystanders' faces before sharing images online. Real estate agents anonymize pedestrians in property photos. Schools and daycare centers obscure children's faces in newsletters and social media — see our guide to blurring faces in photos for best practices. Researchers redact participant faces in published studies. Sellers on marketplaces blur faces in product photos taken in public. Before sharing any photo publicly, also check what metadata it exposes with the Privacy Score checker.

Pixelation replaces each block of pixels with a single averaged color, creating the familiar mosaic or censored look. It is the standard approach for news broadcasts, legal documents, and law enforcement redactions. Gaussian blur applies a smooth convolution filter that gradually fades facial features into an unrecognizable smudge. It looks more natural in casual or editorial contexts — social media posts, blog photos, portfolio images. Both methods are irreversible once the image is saved, meaning the original face data cannot be recovered from the blurred output. For removing hidden metadata like GPS coordinates alongside face blurring, use the EXIF Remover.

The AI model works best on frontal and slightly angled faces in well-lit conditions. It may miss heavily occluded faces (sunglasses, masks, hands covering), extreme profile angles, very small faces in crowd shots, or faces in unusual orientations. Low-resolution images and heavy JPEG compression reduce detection accuracy. If a face is missed, you can re-upload a cropped version focusing on the missed area. For verifying whether photos have been digitally altered before or after blurring, the Authenticity Checker examines metadata for signs of editing software.