Automatic human segmentation
Uses a neural network to segment people in camera images before pixelating them, with a stated distance-related limitation on detection quality.
Person Pixelizer
A free C++ person-pixelation project that anonymizes people in video using OpenCV and neural network segmentation. It is aimed at developers building privacy-focused live video or browser-based computer-vision applications.
Real-time human pixelation for video and web apps
Person Pixelizer is a free real-time privacy anonymization project that pixelates people in video using C++, OpenCV, and neural network segmentation. Its purpose is to detect humans in camera images and obscure them live, helping developers build applications that protect identities during video capture or streaming.
The project is compiled to WebAssembly with Emscripten for browser-friendly deployment. The product page says it includes the complete C++ source code, documentation, build instructions, a pre-trained human-segmentation model, and a precompiled OpenCV WebAssembly module, so buyers can study, customize, and integrate the implementation into their own work.
Core features
Real-time anonymization
Applies pixelation to detected people in live video streams to obscure identities during capture or playback.
WebAssembly deployment
The project is compiled to WebAssembly with Emscripten, which supports browser-based deployment and cross-platform use.
Full source code access
Ships with complete C++ source files, build instructions, and documentation so users can inspect and adapt the implementation.
Bundled runtime assets
Includes a pre-trained segmentation model and a precompiled OpenCV WebAssembly module required by the demo and build workflow.
Code-level configuration
Lets developers set the pixelation strength in code rather than through a separate user-facing control panel.
Where it fits
Privacy filtering in live video
Build a web or app feature that obscures people in live camera feeds to reduce exposure of personal identity.
Computer vision education and experimentation
Prototype or study a practical computer-vision pipeline that combines segmentation, pixelation, and browser deployment.
Commercial product integration
Integrate the project into a larger commercial product where anonymized video is needed, while keeping the implementation under your control.
Cross-platform development
Adapt the code for desktop, mobile, server, or browser-based workflows, using the included source and build instructions as a starting point.
Web demo and proof of concept
Demonstrate a browser-based privacy demo using the provided WebAssembly-oriented implementation and demo workflow.
Pros and Cons
Pros
- Detects and pixelates people automatically in real time.
- Provides full source code, documentation, and build instructions.
- Supports browser-oriented deployment through WebAssembly.
- Can be integrated into commercial desktop, mobile, server, or browser projects according to the FAQ.
- Includes the model and OpenCV WebAssembly module needed for the demo workflow.
Cons
- The product page notes a limitation related to detection distance, so accuracy may vary by scene.
- Support and custom changes are not offered; users are expected to rely on the documentation and demos.
- The workflow requires C++ knowledge and the Emscripten SDK, which may be a barrier for some users.
FAQ
What does Person Pixelizer do?
The product page describes Person Pixelizer as a C++ project that automatically pixelates humans in camera images using OpenCV and neural network segmentation.
What is included with the project?
The source indicates the project includes complete C++ source code, documentation, build instructions, a pre-trained human-segmentation model, and a precompiled OpenCV WebAssembly module.
Can I use it in commercial applications?
Yes. The FAQ says you may integrate the code into your own projects and ship the resulting product commercially, including as binaries or services.
What platform and workflow does it target?
The source says the code is compiled to WebAssembly with Emscripten for web environments, but it also requires C++ knowledge and the Emscripten SDK for compilation.
Are there any notable limitations or support expectations?
The product page notes that the solution has limitations related to distance, and the FAQ says support and custom changes are not provided because these are self-serve products.
Quick Facts
- Category
- Developer Tool
- Primary use
- Real-time person anonymization in video
- Tech stack
- C++, OpenCV, neural network segmentation, Emscripten
- Deployment
- WebAssembly / web applications
- License shape
- Full source included; commercial use allowed for own products, with source redistribution restricted by the FAQ
- Vendor
- Antal.AI
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