python-examples-cv/opticflow.py at master · Irenaeusw/python-examples-cv · GitHub

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#####################################################################

# Example : perform live visualization of optic flow from a video file
# specified on the command line (e.g. python FILE.py video_file) or from
# an attached web camera

# Author : Toby Breckon, toby.breckon@durham.ac.uk

# Copyright (c) 2017 School of Engineering & Computing Science,
#                    Durham University, UK
# License : LGPL - http://www.gnu.org/licenses/lgpl.html

#####################################################################

import cv2
import argparse
import sys
import numpy as np

#####################################################################

keep_processing = True;

# parse command line arguments for camera ID or video file

parser = argparse.ArgumentParser(description='Perform ' + sys.argv[0] + ' example operation on incoming camera/video image')
parser.add_argument("-c", "--camera_to_use", type=int, help="specify camera to use", default=0)
parser.add_argument('video_file', metavar='video_file', type=str, nargs='?', help='specify optional video file')
args = parser.parse_args()

#####################################################################

# draw optic flow visualization on image using a given step size for
# the line glyphs that show the flow vectors on the image

def draw_flow(img, flow, step=8):
    h, w = img.shape[:2]
    y, x = np.mgrid[step/2:h:step, step/2:w:step].reshape(2,-1).astype(int)
    fx, fy = flow[y,x].T
    lines = np.vstack([x, y, x+fx, y+fy]).T.reshape(-1, 2, 2)
    lines = np.int32(lines + 0.5)
    vis = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
    cv2.polylines(vis, lines, 0, (0, 255, 0))
    for (x1, y1), (x2, y2) in lines:
        cv2.circle(vis, (x1, y1), 1, (0, 255, 0), -1)
    return vis

#####################################################################

# define video capture object

cap = cv2.VideoCapture();

# define display window name

windowName = "Dense Optic Flow"; # window name

# if command line arguments are provided try to read video_name
# otherwise default to capture from attached H/W camera

if (((args.video_file) and (cap.open(str(args.video_file))))
    or (cap.open(args.camera_to_use))):

    # create window by name (as resizable)

    cv2.namedWindow(windowName, cv2.WINDOW_NORMAL);

    # if video file successfully open then read an initial frame from video

    if (cap.isOpened):
        ret, frame = cap.read();

    # convert image to grayscale to be previous frame

    prevgray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    while (keep_processing):

        # if video file successfully open then read frame from video

        if (cap.isOpened):
            ret, frame = cap.read();

            # when we reach the end of the video (file) exit cleanly

            if (ret == 0):
                keep_processing = False;
                continue;

        # convert image to grayscale

        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

        # compute dense optic flow using technique of Farneback 2003
        # parameters from example (OpenCV 3.2):
        # https://github.com/opencv/opencv/blob/master/samples/python/opt_flow.py

        flow = cv2.calcOpticalFlowFarneback(prevgray, gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
        prevgray = gray

        # display image with optic flow overlay

        cv2.imshow(windowName, draw_flow(gray, flow))

        # start the event loop - essential

        # cv2.waitKey() is a keyboard binding function (argument is the time in milliseconds).
        # It waits for specified milliseconds for any keyboard event.
        # If you press any key in that time, the program continues.
        # If 0 is passed, it waits indefinitely for a key stroke.
        # (bitwise and with 0xFF to extract least significant byte of multi-byte response)

        key = cv2.waitKey(40) & 0xFF; # wait 40ms (i.e. 1000ms / 25 fps = 40 ms)

        # It can also be set to detect specific key strokes by recording which key is pressed

        # e.g. if user presses "x" then exit  / press "f" for fullscreen display

        if (key == ord('x')):
            keep_processing = False;
        elif (key == ord('f')):
            cv2.setWindowProperty(windowName, cv2.WND_PROP_FULLSCREEN, cv2.WINDOW_FULLSCREEN);

    # close all windows

    cv2.destroyAllWindows()

else:
    print("No video file specified or camera connected.");

#####################################################################