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1. #How to blur a face in a photo in google photos how to
2. #How to blur a face in a photo in google photos driver
3. #How to blur a face in a photo in google photos code

Your face detector will give you the bounding box (x, y)-coordinates of a face in an image. Once you have detected a face, Step #2 is to extract the Region of Interest (ROI): Figure 4: The second step for blurring faces with Python and OpenCV is to extract the face region of interest (ROI).

#How to blur a face in a photo in google photos how to

You can refer to this face detection guide for more information on how to detect faces in an image.

Typical face detectors that you may use include Figure 3: The first step for face blurring with OpenCV and Python is to detect all faces in an image/video ( image source).Īny face detector can be used here, provided that it can produce the bounding box coordinates of a face in an image or video stream. 4 Steps to perform face blurring and anonymization Figure 2: Face blurring with OpenCV and Python can be broken down into four steps.Īpplying face blurring with OpenCV and computer vision is a four-step process. We use face blurring to help protect the identity of a person in an image. What is face blurring, and how can it be used for face anonymization? Figure 1: In this tutorial, we will learn how to blur faces with OpenCV and Python, similar to the face in this example ( image source).įace blurring is a computer vision method used to anonymize faces in images and video.Īn example of face blurring and anonymization can be seen in Figure 1 above - notice how the face is blurred, and the identity of the person is indiscernible. We’ll then review the results of our face blurring and anonymization methods.

#How to blur a face in a photo in google photos driver

Given our two implementations, we’ll create Python driver scripts to apply these face blurring methods to both images and video.

#How to blur a face in a photo in google photos code

Looking for the source code to this post? Jump Right To The Downloads Section Blur and anonymize faces with OpenCV and Python To learn how to blur and anonymize faces with OpenCV and Python, just keep reading! Dataset curation and distribution (e.g., anonymize individuals in dataset).Photo journalism and news reporting (e.g., blur faces of people who did not sign a waiver form).Protecting children online (i.e., blur faces of minors in uploaded photos).Privacy and identity protection in public/private areas.Practical applications of face blurring and anonymization include: īut what if we wanted to do the “opposite” of face recognition? What if we instead wanted to anonymize the face by blurring it, thereby making it impossible to identify the face? Li asks a great question - we often utilize face detection in our projects, typically as the first step in a face recognition pipeline. I’m in charge of creating the dataset but my professor has asked me to “anonymize” each image by detecting faces and then blurring them to ensure privacy is protected and that no face can be recognized (apparently this is a requirement at my institution before we publicly distribute the dataset).ĭo you have any tutorials on face anonymization? How can I blur faces using OpenCV? Hi Adrian, I’m working on a research project for my university. Today’s blog post is inspired by an email I received last week from PyImageSearch reader, Li Wei: In this tutorial, you will learn how to blur and anonymize faces using OpenCV and Python.