def __init__(self, camName, camURL, cameraFunction, dlibDetection,
fpsTweak):
logger.info("Loading Stream From IP Camera: " + camURL)
self.motionDetector = MotionDetector.MotionDetector()
self.faceDetector = FaceDetector.FaceDetector()
self.processing_frame = None
self.tempFrame = None
self.captureFrame = None
self.streamingFPS = 0 # Streaming frame rate per second
self.processingFPS = 0
self.FPSstart = time.time()
self.FPScount = 0
self.motion = False # Used for alerts and transistion between system states i.e from motion detection to face detection
self.people = {} # Holds person ID and corresponding person object
self.trackers = [] # Holds all alive trackers
self.cameraFunction = cameraFunction
self.dlibDetection = dlibDetection # Used to choose detection method for camera (dlib - True vs opencv - False)
self.fpsTweak = fpsTweak # used to know if we should apply the FPS work around when you have many cameras
self.rgbFrame = None
self.faceBoxes = None
self.captureEvent = threading.Event()
self.captureEvent.set()
self.peopleDictLock = threading.Lock(
) # Used to block concurrent access to people dictionary
self.video = cv2.VideoCapture(
camURL
) # VideoCapture object used to capture frames from IP camera
logger.info("We are opening the video feed.")
self.url = camURL
self.camName = camName
if not self.video.isOpened():
# raise Exception("could not open camera or channelinput " + camurl)
self.video.open()
logger.info("Video feed open.")
self.dump_video_info() # logging every specs of the video feed
# Start a thread to continuously capture frames.
# The capture thread ensures the frames being processed are up to date and are not old
self.captureLock = threading.Lock(
) # Sometimes used to prevent concurrent access
self.captureThread = threading.Thread(name='video_captureThread ' +
camURL,
target=self.get_frame)
self.captureThread.daemon = True
self.captureThread.stop = False
self.captureThread.start()
#RdL Load Params from HSConfig.cfg
hsconfigparser = SafeConfigParser()
hsconfigparser.read('HSConfig.cfg')
self.param_cameramode = hsconfigparser.get('MACHINERY', 'cameramode')
logger.info('Video Feed opened in mode: ' + self.param_cameramode)
print('Video Feed opened in mode: ' + self.param_cameramode)
def __init__(self, camURL, cameraFunction, dlibDetection, fpsTweak):
logger.info("Loading Stream From IP Camera: " + camURL)
self.motionDetector = MotionDetector.MotionDetector()
self.faceDetector = FaceDetector.FaceDetector()
self.processing_frame = None
self.tempFrame = None
self.captureFrame = None
self.streamingFPS = 0 # Streaming frame rate per second
self.processingFPS = 0
self.FPSstart = time.time()
self.FPScount = 0
self.motion = False # Used for alerts and transistion between system states i.e from motion detection to face detection
self.people = {} # Holds person ID and corresponding person object
self.trackers = [] # Holds all alive trackers
self.cameraFunction = cameraFunction
self.dlibDetection = dlibDetection # Used to choose detection method for camera (dlib - True vs opencv - False)
self.fpsTweak = fpsTweak # used to know if we should apply the FPS work around when you have many cameras
self.rgbFrame = None
self.faceBoxes = None
self.captureEvent = threading.Event()
self.captureEvent.set()
self.peopleDictLock = threading.Lock(
) # Used to block concurrent access to people dictionary
uri = camURL
latency = 100
width = 1280
height = 720 #738
framerate = 25
#gst_str = ("rtspsrc location={} latency={} ! rtph264depay ! h264parse ! omxh264dec ! nvvidconv ! video/x-raw, width=(int){}, height=(int){}, framerate={}/1, format=(string)BGRx ! videoconvert ! appsink").format(uri, latency, width, height, framerate)
#gst_str = ("rtspsrc location={} latency={} ! queue ! rtph264depay ! queue ! h264parse ! omxh264dec ! nvvidconv ! video/x-raw,format=BGRx ! videoconvert ! video/x-raw,format=BGR ! appsink").format(uri, latency)
gst_str = "rtspsrc location={} ! application/x-rtp, media=video ! rtph264depay ! h264parse ! nvv4l2decoder ! nvvidconv ! video/x-raw, format=BGRx ! videoconvert ! video/x-raw, format=BGR ! appsink".format(
uri)
self.video = cv2.VideoCapture(gst_str, cv2.CAP_GSTREAMER)
#self.video = cv2.VideoCapture(camURL) # VideoCapture object used to capture frames from IP camera
logger.info("We are opening the video feed.")
self.url = camURL
logger.info("Video feed open.")
self.dump_video_info() # logging every specs of the video feed
# Start a thread to continuously capture frames.
# The capture thread ensures the frames being processed are up to date and are not old
self.captureLock = threading.Lock(
) # Sometimes used to prevent concurrent access
self.captureThread = threading.Thread(name='video_captureThread',
target=self.get_frame)
self.captureThread.daemon = True
self.captureThread.start()
self.captureThread.stop = False
def __init__(self, camURL, cameraFunction="detect_recognise_track", dlibDetection=True, fpsTweak=False):
logger.info("Loading Stream From IP Camera: " + camURL)
self.motionDetector = MotionDetector.MotionDetector()
self.faceDetector = FaceDetector.FaceDetector()
self.processing_frame = None
self.tempFrame = None
self.captureFrame = None
self.streamingFPS = 0 # Streaming frame rate per second
self.processingFPS = 0
self.FPSstart = time.time()
self.FPScount = 0
self.motion = False # Used for alerts and transistion between system states i.e from motion detection to face detection
self.people = {} # Holds person ID and corresponding person object
self.trackers = [] # Holds all alive trackers
self.cameraFunction = cameraFunction
self.dlibDetection = dlibDetection # Used to choose detection method for camera (dlib - True vs opencv - False)
self.fpsTweak = fpsTweak # used to know if we should apply the FPS work around when you have many cameras
self.rgbFrame = None
self.faceBoxes = None
self.captureEvent = threading.Event()
self.captureEvent.set()
self.peopleDictLock = threading.Lock() # Used to block concurrent access to people dictionary
if camURL == 'w':
self.video = cv2.VideoCapture(0)
camURL = 0
else:
self.video = cv2.VideoCapture(camURL) # VideoCapture object used to capture frames from IP camera
self.video.set(3, 640)
self.video.set(4, 480)
self.url = camURL
logger.info("We are opening the video feed.")
logger.info("Video feed open.")
# Start a thread to continuously capture frames.
# The capture thread ensures the frames being processed are up to date and are not old
self.captureLock = threading.Lock() # Sometimes used to prevent concurrent access
self.captureThread = threading.Thread(name='video_captureThread',target=self.get_frame)
self.captureThread.daemon = True
self.captureThread.start()
self.captureThread.stop = False
def __init__(self, camURL, cameraFunction, dlibDetection):
print("Loading Stream From IP Camera ", camURL)
self.motionDetector = MotionDetector.MotionDetector()
self.faceDetector = FaceDetector.FaceDetector()
self.processing_frame = None
self.tempFrame = None
self.captureFrame = None
self.streamingFPS = 0 # Streaming frame rate per second
self.processingFPS = 0
self.FPSstart = time.time()
self.FPScount = 0
self.motion = False # Used for alerts and transistion between system states i.e from motion detection to face detection
self.people = {} # Holds person ID and corresponding person object
self.trackers = [] # Holds all alive trackers
self.cameraFunction = cameraFunction
self.dlibDetection = dlibDetection # Used to choose detection method for camera (dlib - True vs opencv - False)
self.rgbFrame = None
self.faceBoxes = None
self.captureEvent = threading.Event()
self.captureEvent.set()
self.peopleDictLock = threading.Lock(
) # Used to block concurrent access to people dictionary
self.video = cv2.VideoCapture(
camURL
) # VideoCapture object used to capture frames from IP camera
self.url = camURL
if not self.video.isOpened():
self.video.open()
# Start a thread to continuously capture frames.
# The capture thread ensures the frames being processed are up to date and are not old
self.captureLock = threading.Lock(
) # Sometimes used to prevent concurrent access
self.captureThread = threading.Thread(name='video_captureThread',
target=self.get_frame)
self.captureThread.daemon = True
self.captureThread.start()
def detectMotion():
print("Ready to detect motion...")
while True:
sharedDictionary["Motion Detected"] = MotionDetector.detectMotion()
def motiondetector(self):
MotionDetector.MotionDetector(self).start()
def main():
#
# Parse arguments.
#
cfg = {'h': False, 'd': False, 'f': '', 'a': 'a1', 'o': '', 't': False}
try:
(opts, args) = getopt.getopt(
sys.argv[1:], 'hdf:a:o:t',
['help', 'debug', 'file', 'algorithm', 'output', 'transform'])
except getopt.GetoptError as err:
print(str(err))
help()
sys.exit(0)
print(opts)
for o, a in opts:
if o in ('-h', '--help'):
cfg['h'] = True
elif o in ('-d', '--debug'):
cfg['d'] = True
elif o in ('-f', '--file'):
cfg['f'] = a
elif o in ('-a', '--algorithm'):
cfg['a'] = a
elif o in ('-o', '--output'):
cfg['o'] = a
elif o in ('-t', '--transform'):
cfg['t'] = True
else:
help()
sys.exit(0)
if cfg['h']:
help()
sys.exit(0)
#
# Build a LabelImage object.
#
if cfg['a'] == 'a1':
labelImage = LabelImageCv2.LabelImage(True)
elif cfg['a'] == 'a2':
labelImage = LabelImageSki.LabelImage(True)
else:
help()
sys.exit(0)
#
# Open file or camera.
#
if cfg['f'] != '':
cam = cv2.VideoCapture(cfg['f'])
else:
cam = cv2.VideoCapture(0)
if cfg['o'] != '':
outputFn = cfg['o']
(grabbed, frame) = cam.read()
(fheight, fwidth, _) = frame.shape
print(fwidth, fheight)
fourcc = cv2.VideoWriter_fourcc(*'XVID')
out = cv2.VideoWriter(outputFn, fourcc, 20.0, (fwidth, fheight))
#fn = 'IMG_4912.m4v'
#cam = cv2.VideoCapture(fn)
winName = "Movement Indicator"
cv2.namedWindow(winName)
md = MotionDetector.MotionDetector(cam)
md.readFirstFrame()
saticCount = 0
lastStatic = False
isStatic = False
labelTrigger = False
if cfg['t']:
maxApprox = None
seq = 0
writeSeq = 0
while True:
labeledImage = None
transformedImage = None
displayedFrame = None
whiteFrame = None
#time.sleep(0.01)
if cfg['t']:
if maxApprox is None:
labelImage.processImages = []
maxApprox = labelImage.getMaxApprox(md.frame)
if maxApprox is not None:
md.frame = labelImage.transform(md.frame, maxApprox, 640, 480)
if cfg['o']:
out.write(md.frame)
print('Write frame ', writeSeq)
writeSeq += 1
lastStatic = isStatic
if not md.isMotion():
saticCount += 1
if saticCount >= 10:
saticCount = 0
isStatic = True
else:
isStatic = False
labelTrigger = False
if not lastStatic and isStatic:
labelTrigger = True
title = "lastStatic = %d, isStatic = %d, labelTrigger = %d" % (
lastStatic, isStatic, labelTrigger)
labelImage.processImages = []
if labelTrigger:
labelImage.handle(md.frame, False)
displayedFrame = labelImage.finalImage
whiteFrame = labelImage.whiteImage
if not isStatic:
displayedFrame = md.frame
whiteFrame = md.frame.copy()
whiteFrame.fill(255)
if cfg['t']:
if transformedImage is not None:
cv2.imshow("Transform", transformedImage)
if labeledImage is not None:
cv2.imshow("2 Before Original", labeledImage)
if displayedFrame is not None:
cv2.putText(displayedFrame, title,
(10, displayedFrame.shape[0] - 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
cv2.imshow("Final", displayedFrame)
'''
if cfg['o']:
out.write(displayedFrame)
print('Write frame ', writeSeq)
writeSeq += 1
'''
if whiteFrame is not None:
cv2.imshow("White", whiteFrame)
#cv2.imshow("Original", md.frame)
#cv2.imshow("Black", labelImage.blackImage)
#cv2.imshow(winName, md.diffImage)
#
# Read next frame
#
md.readNextFrame()
seq += 1
key = cv2.waitKey(
1) # wait 50 milliseconds before each frame is written.
if key == 27: # ESC
cv2.destroyWindow(winName)
break
if cfg['o']:
out.release()
print('seq = ', seq)
print('writeSeq = ', writeSeq)
print("Goodbye")