Person Blocker is a small open-source tool that automatically “blocks” people in images — covering them with the black censor bars made famous by Black Mirror — using a pretrained neural network. Point it at a photo and it detects the people in it and obscures them, no manual editing required. Created by Max Woolf, the project has 2,009 stars on GitHub.
Person Blocker is a delightfully focused utility: one job, done automatically. Under the hood it runs a pretrained object-detection model to locate people in an image, then draws the signature black block over each detected person. It is equal parts practical anonymisation trick and pop-culture homage, and its compact codebase makes it a friendly example of applying a detection model end to end — load image, detect, draw, save.
The tool became a small viral favourite because the output is instantly recognisable — the menacing black rectangle from the ‘White Christmas’ episode of Black Mirror — and because it works on ordinary photos with no tuning. It also quietly demonstrates a real point: the same detection models used for photo organisation can just as easily be used to protect people’s privacy at scale.
Person Blocker is free and open source on GitHub. There are no fees or accounts; you run it on your own machine with your own images.
Person Blocker suits photographers, meme-makers and privacy-minded users who want a fast way to obscure people in photos, plus developers looking for a minimal detection demo. The repository was last updated in 2022, so treat it as a fun, finished utility rather than an evolving platform.