import cv2
import face_recognition
import imutils

input_video = cv2.VideoCapture('clowns.mp4')

clown = cv2.imread("clown-face-emoji-by-twitter.png")
fps = int(input_video.get(5))
out = cv2.VideoWriter('outpy.avi', cv2.VideoWriter_fourcc('M', 'J', 'P', 'G'), fps, (int(input_video.get(4)), int(input_video.get(3))))


def clownify():

    while True:
        # Grab a single frame of video
        ret, frame = input_video.read()

        # Quit when the input video file ends
        if not ret:
            break

        frame = imutils.rotate_bound(frame, 90)
        frame = cv2.flip(frame, 1)
        # Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
        rgb_frame = frame[:, :, ::-1]

        # Find all the faces and face encodings in the current frame of video
        face_locations = face_recognition.face_locations(rgb_frame)

        # Label the results
        for (top, right, bottom, left) in face_locations:

            resized_clown = cv2.resize(clown, (right - left, bottom - top), interpolation=cv2.INTER_AREA)
            # Draw a box around the face
            cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
            # put a clown over the face
            frame[top:bottom, left:right] = resized_clown
        # write frame out to video
        out.write(frame)
        # quit if q keypress is detected
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
    # cleanup stuff
    input_video.release()
    cv2.destroyAllWindows()


# function call because I'm a dumbass
clownify()