EZ-VIDEO FACE BLUR In A Privacy Conscious World

I love small projects, micro services, privacy, and empowering the user. When I saw this tweet I thought that this sounded like a great evening problem to solve; whats the easiest way I could accomplish this?

Lets Break It Down!

• Faces can be detected in video and images.
• A video file is a collection of still images.
• Detected faces can be blurred.
• Images can be combined to video.

This seems like a pretty straight forward method of accomplishing our goal. Not trying to reinvent the wheel I decided to use tried and true tools in addition to some python and bash code.

FFmpeg is a free and open-source project consisting of a vast software suite of libraries and programs for handling video, audio, and other multimedia files and streams.

Using FFmpeg we're able to quickly and easily explode a video into images and set them up for processing.

#!/bin/bash
echo "{EXPLODE}"
mkdir -p explode;
FRAMERATE=$(ffmpeg -i $1 2>&1 | sed -n "s/.*, \(.*\) fp.*/\1/p")
ffmpeg -i $1 -r 1 explode/%04d.jpeg -hide_banner;

With our video frames pulled out we can process each one through some code that will identify and apply a blurring filter to a face.

frame = cv2.imread(currentFile)
# Resize frame of video to 1/4 size for faster face detection processing
small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
# Find all the faces and face encodings in the current frame of video
face_locations = face_recognition.face_locations(small_frame)
# Display the results

for top, right, bottom, left in face_locations:
    # Scale back up face locations
    top *= 4
    right *= 4
    bottom *= 4
    left *= 4

    # Extract the region of the image that contains the face
    face_image = frame[top:bottom, left:right]

    # Blur the face image
    face_image = cv2.GaussianBlur(face_image, (99, 99), 30)

    # Put the blurred face region back into the frame image
    frame[top:bottom, left:right] = face_image

# Write the resulting image
cv2.imwrite("./blur/"+ str(currentFile).split('/')[1] , frame)

Snippet of ..master/blur.py

Nice! We're most of the way there, all we have to do is stitch the video back together and we'll have a video with the faces blurred out.

Back to using FFmpeg and providing it a folder of processed images we can easily generate a video file.

ffmpeg -i ./blur/%04d.jpeg -vcodec mpeg4 -r 25 ./out.avi;

This method worked well for the proof of concept I wanted to produce. This is not a perfect turn-key method to blur faces from videos. There can be issues with the FFmpeg command based on file input. There are cases where a face is turned to where it fails detection but is still very clearly identifiable.

This project can be found @ https://echohtp.github.io/EZ-VideoFaceBlur/

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