53 lines
1.7 KiB
Python
53 lines
1.7 KiB
Python
import face_recognition
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import cv2
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# This is a demo of blurring faces in video.
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# PLEASE NOTE: This example requires OpenCV (the `cv2` library) to be installed only to read from your webcam.
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# OpenCV is *not* required to use the face_recognition library. It's only required if you want to run this
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# specific demo. If you have trouble installing it, try any of the other demos that don't require it instead.
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# Get a reference to webcam #0 (the default one)
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video_capture = cv2.VideoCapture(0)
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# Initialize some variables
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face_locations = []
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while True:
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# Grab a single frame of video
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ret, frame = video_capture.read()
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# Resize frame of video to 1/4 size for faster face detection processing
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small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
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# Find all the faces and face encodings in the current frame of video
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face_locations = face_recognition.face_locations(small_frame, model="cnn")
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# Display the results
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for top, right, bottom, left in face_locations:
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# Scale back up face locations since the frame we detected in was scaled to 1/4 size
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top *= 4
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right *= 4
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bottom *= 4
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left *= 4
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# Extract the region of the image that contains the face
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face_image = frame[top:bottom, left:right]
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# Blur the face image
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face_image = cv2.GaussianBlur(face_image, (99, 99), 30)
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# Put the blurred face region back into the frame image
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frame[top:bottom, left:right] = face_image
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# Display the resulting image
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cv2.imshow('Video', frame)
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# Hit 'q' on the keyboard to quit!
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if cv2.waitKey(1) & 0xFF == ord('q'):
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break
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# Release handle to the webcam
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video_capture.release()
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cv2.destroyAllWindows()
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