canny.py

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# Example :  canny edge detection for a 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) 2016 School of Engineering & Computing Science,
#                    Durham University, UK
# License : LGPL - http://www.gnu.org/licenses/lgpl.html

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import cv2
import argparse
import sys

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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()

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# this function is called as a call-back everytime the trackbar is moved
# (here we just do nothing)

def nothing(x):
    pass

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# define video capture object

cap = cv2.VideoCapture();

# define display window name

windowName = "Live Camera Input"; # window name
windowName2 = "Canny Edges"; # 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);
    cv2.namedWindow(windowName2, cv2.WINDOW_NORMAL);

    # add some track bar controllers for settings

    lower_threshold = 25;
    cv2.createTrackbar("lower", windowName2, lower_threshold, 255, nothing);
    upper_threshold = 120;
    cv2.createTrackbar("upper", windowName2, upper_threshold, 255, nothing);
    smoothing_neighbourhood = 3;
    cv2.createTrackbar("smoothing", windowName2, smoothing_neighbourhood, 15, nothing);
    sobel_size = 3; # greater than 7 seems to crash
    cv2.createTrackbar("sobel size", windowName2, sobel_size, 7, nothing);


    while (keep_processing):

        # if video file successfully open then read frame from video

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

        # get parameters from track bars

        lower_threshold = cv2.getTrackbarPos("lower", windowName2);
        upper_threshold = cv2.getTrackbarPos("upper", windowName2);
        smoothing_neighbourhood = cv2.getTrackbarPos("smoothing", windowName2);
        sobel_size = cv2.getTrackbarPos("sobel size", windowName2);

        # check neighbourhood is greater than 3 and odd

        smoothing_neighbourhood = max(3, smoothing_neighbourhood);
        if not(smoothing_neighbourhood % 2):
            smoothing_neighbourhood = smoothing_neighbourhood + 1;

        sobel_size = max(3, sobel_size);
        if not(sobel_size % 2):
            sobel_size = sobel_size + 1;


        # convert to grayscale

        gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY);

        # performing smoothing on the image using a 5x5 smoothing mark (see manual entry for GaussianBlur())

        smoothed = cv2.GaussianBlur(gray_frame,(smoothing_neighbourhood,smoothing_neighbourhood),0);

        # perform canny edge detection

        canny = cv2.Canny(smoothed, lower_threshold, upper_threshold, apertureSize=sobel_size);

        # display image

        cv2.imshow(windowName,frame);
        cv2.imshow(windowName2,canny)

        # 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(windowName2, cv2.WND_PROP_FULLSCREEN, cv2.WINDOW_FULLSCREEN);

    # close all windows

    cv2.destroyAllWindows()

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

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