Blur and Anonymize Faces using OpenCV Deep Learning Model
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Face blurring is a computer vision method used to anonymize faces in images and video. In this project, I have used Deep Learning based Face Detector to detect the face we need to blur. OneAPI will be incorporated to make using the code easier in every machine. ...learn more
Project status: Concept
oneAPI, Artificial Intelligence
Intel Technologies
oneAPI
Overview / Usage
Practical applications of face blurring and anonymization include:
- Privacy and identity protection in public/private areas
- Protecting children online (i.e., blur faces of minors in uploaded photos)
- Photo journalism and news reporting (e.g., blur faces of people who did not sign a waiver form)
- Dataset curation and distribution (e.g., anonymize individuals in dataset)
Methodology / Approach
The process of face blurring is a 4-step process. The first step is to perform face detection. In this case, I have used to Deep Lea Face Det of OpenCV. After the face is detected, the ROI is extracted. Then various blurring techniques like Gaussian Blur and Pixelated Blur are applied. The last step involves adding the blurred face to the original image.
Technologies Used
OpenCV, Python 3, OneAPI.
Repository
https://github.com/DEBANJANAB/Face-Blur-and-Anonymization-using-OpenCV