import contextlib
import time
import cv2


def create_video_writer(video_cap, output_filename):

    # grab the width, height, and fps of the frames in the video stream.
    frame_width = int(video_cap.get(cv2.CAP_PROP_FRAME_WIDTH))
    frame_height = int(video_cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
    fps = int(video_cap.get(cv2.CAP_PROP_FPS))

    # initialize the FourCC and a video writer object
    fourcc = cv2.VideoWriter_fourcc(*'MP4V')
    writer = cv2.VideoWriter(output_filename, fourcc, fps,
                             (frame_width, frame_height))

    return writer


def iter_frames(video_cap):
    while 1:
        ret, frame = video_cap.read()
        if not ret:
            return
        yield frame, video_cap.get(cv2.CAP_PROP_POS_MSEC)


@contextlib.contextmanager
def time_tracker():
    start = time.monotonic()
    yield
    end = time.monotonic()
    print(f"Time to process 1 frame: {(end-start) * 1000:.0f} milliseconds")