This C++ project automatically pixelates humans in camera images. Leveraging OpenCV and a neural network segmentation model, this program detects and obscures people in real-time video streams. Compiled to WebAssembly using Emscripten, it seamlessly integrates into web applications for cross-platform compatibility.

The key features include automatic human segmentation utilizing a neural network to accurately segment humans in camera images, though the solution has limitations in terms of distance. It provides real-time pixelation that instantly pixelates detected humans to protect identities during live video feeds, with pixelation strength that can be set in the code. The project offers web integration compiled with Emscripten for easy deployment in web environments without sacrificing performance. It also provides full source code access with purchase including the complete C++ source code for full transparency and customization.

The project works by using a neural network segmentation model integrated with OpenCV in C++ to process camera images in real-time. It is compiled to WebAssembly using Emscripten, allowing it to run efficiently in web browsers while maintaining the performance of native code.

Benefits include protecting personal identities in applications with a powerful, real-time human pixelation tool. It is ideal for developers seeking to enhance privacy in video processing applications, educational purposes for learning about real-time image processing and neural networks, and projects that require human detection and anonymization on the web.

The target users are developers and educators. It requires knowledge of C++ programming and basic understanding of neural networks, along with the Emscripten SDK for compiling to WebAssembly. The purchase includes complete C++ source code files, instructions for compiling with Emscripten, a pre-trained neural network model for human segmentation, and a precompiled OpenCV WebAssembly module.