Interaction-without-Interac.../server/motion_detector_old.py

130 lines
3.8 KiB
Python

# USAGE
# python motion_detector.py
# python motion_detector.py --video videos/example_01.mp4
# import the necessary packages
from imutils.video import VideoStream
import argparse
import datetime
import imutils
import time
import cv2
def increase_brightness(img, value=30):
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
h, s, v = cv2.split(hsv)
lim = 255 - value
v[v > lim] = 255
v[v <= lim] += value
final_hsv = cv2.merge((h, s, v))
img = cv2.cvtColor(final_hsv, cv2.COLOR_HSV2BGR)
return img
# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video", help="path to the video file")
ap.add_argument("-amin", "--min-area", type=int, default=3000, help="minimum area size")
ap.add_argument("-amax", "--max-area", type=int, default=10000, help="minimum area size")
args = vars(ap.parse_args())
# if the video argument is None, then we are reading from webcam
args["video"] = "http://192.168.178.53:8000/stream.mjpg"
args["video"] = "./videos/example_02.mp4"
vs = cv2.VideoCapture(args["video"])
counter = 0
threashold = 50
delay = 2
framerate = 30
# initialize the first frame in the video stream
firstFrame = None
# loop over the frames of the video
while True:
# grab the current frame and initialize the occupied/unoccupied
# text
frame = vs.read()
frame = frame if args.get("video", None) is None else frame[1]
text = "Unoccupied"
# if the frame could not be grabbed, then we have reached the end
# of the video
if frame is None:
break
# resize the frame, convert it to grayscale, and blur it
frame = imutils.resize(frame, width=500)
#frame = increase_brightness(frame, value=50)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (31, 31), 0)
# if the first frame is None, initialize it
if firstFrame is None:
firstFrame = gray
continue
# compute the absolute difference between the current frame and
# first frame
frameDelta = cv2.absdiff(gray, firstFrame)
thresh = cv2.threshold(frameDelta, threashold, 255, cv2.THRESH_BINARY)[1]
# dilate the thresholded image to fill in holes, then find contours
# on thresholded image
thresh = cv2.dilate(thresh, None, iterations=2)
cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = imutils.grab_contours(cnts)
# loop over the contours
for c in cnts:
# if the contour is too small, ignore it
if cv2.contourArea(c) < args["min_area"]:
continue
if cv2.contourArea(c) > args["max_area"]:
continue
# compute the bounding box for the contour, draw it on the frame,
# and update the text
print(cv2.contourArea(c))
(x, y, w, h) = cv2.boundingRect(c)
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
text = "Occupied"
# draw the text and timestamp on the frame
cv2.putText(frame, "Room Status: {}".format(text), (10, 20),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
cv2.putText(frame, datetime.datetime.now().strftime("%A %d %B %Y %I:%M:%S%p"),
(10, frame.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1)
# show the frame and record if the user presses a key
cv2.imshow("Security Feed", frame)
cv2.imshow("Thresh", thresh)
cv2.imshow("Frame Delta", frameDelta)
img_yuv = cv2.cvtColor(frame, cv2.COLOR_BGR2YUV)
# equalize the histogram of the Y channel
img_yuv[:,:,0] = cv2.equalizeHist(img_yuv[:,:,0])
# convert the YUV image back to RGB format
img_output = cv2.cvtColor(img_yuv, cv2.COLOR_YUV2BGR)
cv2.imshow("equalized", img_output)
key = cv2.waitKey(1) & 0xFF
# if the `q` key is pressed, break from the lop
if key == ord("q"):
break
counter+=1
#if counter % (framerate * delay) == 0:
# firstFrame = gray
# cleanup the camera and close any open windows
vs.stop() if args.get("video", None) is None else vs.release()
cv2.destroyAllWindows()