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abs_difference.py
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abs_difference.py
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#####################################################################
# Example : simple image differencing and contrast via multiplication
# 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) 2015 School of Engineering & Computing Science,
# Copyright (c) 2019 Dept Computer Science,
# Durham University, UK
# License : LGPL - http://www.gnu.org/licenses/lgpl.html
#####################################################################
import cv2
import argparse
import sys
#####################################################################
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(
"-r",
"--rescale",
type=float,
help="rescale image by this factor",
default=1.0)
parser.add_argument(
'video_file',
metavar='video_file',
type=str,
nargs='?',
help='specify optional video file')
args = parser.parse_args()
use_greyscale = False
#####################################################################
# this function is called as a call-back everytime the trackbar is moved
# (here we just do nothing)
def nothing(x):
pass
#####################################################################
# define video capture object
try:
# to use a non-buffered camera stream (via a separate thread)
if not (args.video_file):
import camera_stream
cap = camera_stream.CameraVideoStream(use_tapi=False)
else:
cap = cv2.VideoCapture() # not needed for video files
except BaseException:
# if not then just use OpenCV default
print("INFO: camera_stream class not found - camera input may be buffered")
cap = cv2.VideoCapture()
# define display window name
window_name = "Live Camera Input" # window name
window_name2 = "Difference Image" # window name
# if command line arguments are provided try to read video_file
# 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 windows by name (as resizable)
cv2.namedWindow(window_name, cv2.WINDOW_NORMAL)
cv2.namedWindow(window_name2, cv2.WINDOW_NORMAL)
# add some track bar controllers for settings
contrast = 1
cv2.createTrackbar("contrast", window_name2, contrast, 30, nothing)
fps = 25
cv2.createTrackbar("fps", window_name2, fps, 25, nothing)
threshold = 0
cv2.createTrackbar("threshold", window_name2, threshold, 255, nothing)
# if video file or camera successfully open then read frame from video
if (cap.isOpened):
ret, frame = cap.read()
# rescale if specified
if (args.rescale != 1.0):
frame = cv2.resize(frame, (0, 0), fx=args.rescale, fy=args.rescale)
# make a deep copy of this (as all camera frames otherwise reside
# in the same portion of allocated memory)
prev_frame = frame.copy()
while (keep_processing):
# if video file or camera 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
# rescale if specified
if (args.rescale != 1.0):
frame = cv2.resize(
frame, (0, 0), fx=args.rescale, fy=args.rescale)
if (use_greyscale):
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# if the previous frame we stored also has 3 channels (colour)
if (len(prev_frame.shape) == 3):
# convert it, otherwise absdiff() will break
prev_frame = cv2.cvtColor(prev_frame, cv2.COLOR_BGR2GRAY)
# performing absolute differencing between consecutive frames
diff_img = cv2.absdiff(prev_frame, frame)
# retrieve the contrast setting from the track bar
contrast = cv2.getTrackbarPos("contrast", window_name2)
# multiple the result to increase the contrast (so we can see small
# pixel changes)
brightened_img = diff_img * contrast
# display images
cv2.imshow(window_name, frame)
# threshold the image if its in grayscale and we have a valid threshold
threshold = cv2.getTrackbarPos("threshold", window_name2)
if (use_greyscale and (threshold > 0)):
# display thresholded image if threshold > 0
# thresholding : if pixel > (threshold value) set to 255 (white),
# otherwise set to 0 (black)
ret, thresholded_img = cv2.threshold(
brightened_img, 127, 255, cv2.THRESH_BINARY)
cv2.imshow(window_name2, thresholded_img)
else:
# otherwise just display the non-thresholded one
cv2.imshow(window_name2, brightened_img)
# start the event loop - essential
# cv2.waitKey() is a keyboard binding function (argument is the time in
# ms). 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)
fps = cv2.getTrackbarPos("fps", window_name2)
# wait T ms (i.e. 1000ms / 25 fps = 40 ms)
key = cv2.waitKey(int(1000 / max(1, fps))) & 0xFF
# It can also be set to detect specific key strokes by recording which
# key is pressed
# e.g. if user presses "x" then exit
if (key == ord('x')):
keep_processing = False
elif (key == ord('g')):
# toggle grayscale usage (when they press 'g')
use_greyscale = not (use_greyscale)
# if the previous frame we stored also has 3 channels (colour)
if (len(prev_frame.shape) != 3):
# convert it to just copying the gray information to all of the
# three channels (this is a hack), otherwise absdiff() will
# break
prev_frame = cv2.cvtColor(prev_frame, cv2.COLOR_GRAY2BGR)
else:
# make a deep copy of the current frame (as all camera frames
# otherwise reside in the same portion of allocated memory)
prev_frame = frame.copy()
# close all windows
cv2.destroyAllWindows()
else:
print("No video file specified or camera connected.")
#####################################################################