face_blur_circle.py

# Using a circular mask as the blur area to automatically blur the face in a video, giving it a more cleaner look. 
# We're using OpenCV, and Dlib with Python.
# See tutorial here: https://youtu.be/1p1lUyLGB2E

import numpy as np
import cv2
import dlib

video_capture = cv2.VideoCapture(1)
detector = dlib.get_frontal_face_detector()

blurred = False
framed = False

while True:
    # Capture frame-by-frame
    ret, frame = video_capture.read()
    # create a temp image and a mask to work on
    temp_img = frame.copy()
    mask_shape = (frame.shape[0], frame.shape[1], 1)
    mask = np.full(mask_shape, 0, dtype=np.uint8)

    if (ret):
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

        rects = detector(gray, 0)

        for rect in rects:
            x = rect.left()
            y = rect.top()
            x1 = rect.right()
            y1 = rect.bottom()
            h = rect.height()
            w = rect.width()

            if blurred:
                temp_img[y:y1, x:x1] = cv2.blur(temp_img[y:y1, x:x1], (25, 25))

            # create the circle in the mask and in the temp_img, notice the one in the mask is full
            cv2.circle(mask, (int((x + x + w)/2), int((y + y + h)/2)), int(h / 2), (255), -1)
            
            if framed:
                cv2.circle(temp_img, ( int((x + x + w )/2), int((y + y + h)/2 )), int (h / 2), (0, 255, 0), 5)

        # apply the mask and combine
        mask_inv = cv2.bitwise_not(mask)
        img_bg = cv2.bitwise_and(frame, frame, mask=mask_inv)
        img_fg = cv2.bitwise_and(temp_img, temp_img, mask=mask)
        combined = cv2.add(img_bg, img_fg)

        # Display the resulting frame
        cv2.imshow('Video Feed', combined)

    ch = 0xFF & cv2.waitKey(1)

    # press "b" to toggle blurring.
    if ch == ord("b"):
        blurred = not blurred

    # press "f" to toggle the frame.
    if ch == ord("f"):
        framed = not framed

    # press "q" to quit the program.
    if ch == ord('q'):
        break

# When everything is done, release the capture
video_capture.release()
cv2.destroyAllWindows()