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.
Free C++ project for real-time person pixelation in video with OpenCV and neural network segmentation, for privacy-focused live video and browser 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.
Uses a neural network to segment people in camera images before pixelating them, with a stated distance-related limitation on detection quality.
Applies pixelation to detected people in live video streams to obscure identities during capture or playback.
The project is compiled to WebAssembly with Emscripten, which supports browser-based deployment and cross-platform use.
Ships with complete C++ source files, build instructions, and documentation so users can inspect and adapt the implementation.
Includes a pre-trained segmentation model and a precompiled OpenCV WebAssembly module required by the demo and build workflow.
Lets developers set the pixelation strength in code rather than through a separate user-facing control panel.
Build a web or app feature that obscures people in live camera feeds to reduce exposure of personal identity.
Prototype or study a practical computer-vision pipeline that combines segmentation, pixelation, and browser deployment.
Integrate the project into a larger commercial product where anonymized video is needed, while keeping the implementation under your control.
Adapt the code for desktop, mobile, server, or browser-based workflows, using the included source and build instructions as a starting point.
Demonstrate a browser-based privacy demo using the provided WebAssembly-oriented implementation and demo workflow.
The product page describes Person Pixelizer as a C++ project that automatically pixelates humans in camera images using OpenCV and neural network segmentation.
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.
Yes. The FAQ says you may integrate the code into your own projects and ship the resulting product commercially, including as binaries or services.
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.
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.
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