diff --git a/examples/blur_faces_on_webcam.py b/examples/blur_faces_on_webcam.py
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+++ b/examples/blur_faces_on_webcam.py
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+import face_recognition
+import cv2
+
+# This is a demo of blurring faces in video.
+
+# PLEASE NOTE: This example requires OpenCV (the `cv2` library) to be installed only to read from your webcam.
+# OpenCV is *not* required to use the face_recognition library. It's only required if you want to run this
+# specific demo. If you have trouble installing it, try any of the other demos that don't require it instead.
+
+# Get a reference to webcam #0 (the default one)
+video_capture = cv2.VideoCapture(0)
+
+# Initialize some variables
+face_locations = []
+
+while True:
+    # Grab a single frame of video
+    ret, frame = video_capture.read()
+
+    # 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, model="cnn")
+
+    # Display the results
+    for top, right, bottom, left in face_locations:
+        # Scale back up face locations since the frame we detected in was scaled to 1/4 size
+        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
+
+    # Display the resulting image
+    cv2.imshow('Video', frame)
+
+    # Hit 'q' on the keyboard to quit!
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+# Release handle to the webcam
+video_capture.release()
+cv2.destroyAllWindows()