JUNGBAE009

JUNGBAE009 / faceblur-anti-ai

Public

A single file Python module that automatically blurs faces with YOLO for privacy protection.

12
1
85% credibility
Found May 17, 2026 at 12 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

This is a privacy protection tool that automatically blurs people's faces in images and videos. You give it a picture or video, it uses AI to find anyone in the frame, and it applies a smooth blur to just their head and face area. The tool is designed to be cautious—if something goes wrong during processing, it blurs everything rather than accidentally exposing raw content. It's a single Python file that works offline, makes no network connections, and leaves no trace of the original unprotected frames.

How It Works

1
🔍 You discover a privacy need

You have photos or videos you need to share, but you want to protect the people in them from being identified.

2
📦 You get the tool ready

You download the single Python file and install a few common tools it needs to work.

3
🤖 You connect an AI detector

You point the tool to a detection model that can recognize people in pictures.

4
🖼️ You drop in your media

You give the tool your image or video file and tell it where to save the protected version.

5
👤 The AI finds everyone

The tool scans through your media and locates each person, then focuses on their head and face area.

6
Smart protection kicks in
👥
People were found

Only the detected face regions get blurred, keeping the rest of your image clear.

🌫️
No people detected

If the AI finds nothing, the tool can either leave the image alone or blur everything for safety.

✅ Your privacy-protected media is ready

The tool saves your processed image or video to the destination you chose, with all faces safely blurred.

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AI-Generated Review

What is faceblur-anti-ai?

This is a Python module that automatically blurs faces and heads in images and videos for privacy protection. It uses YOLO person detection to find people, then applies a soft elliptical blur to the upper portion of each detected person. The module handles both single images and videos, writing processed output to files while never exposing raw frames through its API. It includes fail-closed behavior by default, meaning if detection fails or no person is found, it blurs the entire frame rather than returning the original.

Why is it gaining traction?

The single-file design makes it trivial to drop into any Python project without package installation or complex setup. Privacy-first defaults mean you get blur-first behavior without configuration. The soft elliptical blur masks avoid the harsh rectangular look of basic censoring. No telemetry, network calls, or logging of raw frames appeals to security-conscious developers building pipelines for sensitive content.

Who should use this?

Developers building video processing pipelines that need to protect subject privacy before storage or distribution. Security teams automating footage anonymization. Researchers working with datasets where faces should not be visible. Anyone running YOLO-based person detection who wants an easy privacy layer on top.

Verdict

This is a well-documented, thoughtfully designed privacy tool with a clean API and sensible defaults. However, with only 12 stars and no visible test coverage, it remains early-stage and unproven at scale. The credibility score of 0.85% reflects this limited community validation. Worth evaluating for non-critical pipelines, but validate detection accuracy against your specific media before production deployment.

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