---
title: "How Google/Apple Maps Blur License Plates and Faces"
description: "Explore how Google/Apple Maps blur sensitive data on Street View."
image: "https://assets.bytebytego.com/diagrams/0347-street-view-blurring-system.png"
createdAt: "2024-03-02"
draft: false
categories:
  - how-it-works
tags:
  - "Machine Learning"
  - "Image Processing"
---

![](https://assets.bytebytego.com/diagrams/0347-street-view-blurring-system.png)

The diagram below presents a possible solution that might work in an interview setting.

The high-level architecture is broken down into three stages:

*   Data pipeline - prepare the training data set
*   Blurring pipeline - extract and classify objects and blur relevant objects, for example, license plates and faces.
*   Serving pipeline - serve blurred street view images to users.

## Data Pipeline

Step 1: We get the annotated dataset for training. The objects are marked in bounding boxes.

Steps 2-4: The dataset goes through preprocessing and augmentation to be normalized and scaled.

Steps 5-6: The annotated dataset is then used to train the machine learning model, which is a 2-stage network.

## Blurring Pipeline

Steps 7-10: The street view images go through preprocessing, and object boundaries are detected in the images. Then sensitive objects are blurred, and the images are stored in an object store.

## Serving Pipeline

Step 11: The blurred images can now be retrieved by users.