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Camera Surveillance System with OpenCV

Guangzhou, China

Github Repository

This Project is going to use PyQt6 to build a Desktop app connected to an OpenCV backend to process an INSTAR IP camera RTSP livestream and perform an Object Detection:

pip install pyqt6 pyqt6-tools opencv-python

You should now be able to start the Qt Designer by typing designer:

Camera Surveillance System with OpenCV

Buidling the User Interface​

You can load the UI file and edit the user interface according to your needs:

Camera Surveillance System with OpenCV

Backend Code​

In the previous step we generated an XML file with the ending .ui. We can now write a Python script that will start a Qt window application using this definition file:

from PyQt6.QtCore import *
from PyQt6.QtGui import *
from PyQt6.QtWidgets import *
from PyQt6.uic import loadUiType

import sys

# load ui definition from Qt designer
ui, _ = loadUiType('opencv-pyqt-dvr.ui')

# initialize application
class DvrDashboard(QMainWindow, ui):
    def __init__(self):
        QMainWindow.__init__(self)
        self.setupUi(self)

# execute the Qt window
def main():
    app = QApplication(sys.argv)
    window = DvrDashboard()
    window.show()
    app.exec()

# start
if __name__ == '__main__':
    main()

Handling UI Interactions​

Next we need to provide functions that catch button presses inside the Qt application window and execute some code in our backend:

# initialize application
class DvrDashboard(QMainWindow, ui):
    def __init__(self):
        QMainWindow.__init__(self)
        self.setupUi(self)
        # handle clicks on button "monitoring"
        self.monitoring.clicked.connect(self.get_livestream)
        # handle clicks on button "exit"
        self.exit.clicked.connect(self.close_window)

    def get_livestream(self):
        print("INFO :: Connecting to IP Camera")

    def close_window(self):
        print("WARNING :: Application shutdown")

Getting the Livevideo​

I will use an INSTAR IP camera's RTSP Stream to feed OpenCV a live video:

def get_livestream(self):
    print("INFO :: Connecting to IP Camera")
    cap = cv2.VideoCapture(RTSP_URL, cv2.CAP_FFMPEG)

    if not cap.isOpened():
        print('ERROR :: Cannot open RTSP stream')
        exit(-1)

    while True:
        success, img = cap.read()
        cv2.imshow(RTSP_URL, img)

        if cv2.waitKey(1) == 27:  # Keep running until you press `esc`
            break
        
    cap.release()
    cv2.destroyAllWindows()

Motion Detection​

For motion detection we can take a second still frame from our camera and compare it to the first one. As long as they both match no motion happened between both captures:

while True:
    # get frame from livestream
    success, img = cap.read()
    # get second frame for motion detection
    _, val_img = cap.read()
    # get absolute difference between both frames
    delta = cv2.absdiff(img, val_img)
    # find contours in delta for moving object location
    grayscale  = cv2.cvtColor(delta, cv2.COLOR_BGR2GRAY)
    blur = cv2.GaussianBlur(grayscale, (5,5), 0)
    canny = cv2.Canny(blur, 35, 75)
    dilated = cv2.dilate(canny, None, iterations=3)
    contours, _ = cv2.findContours(dilated, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    
    for ctr in contours:
        # filter small objects
        if cv2.contourArea(ctr) < 5000:
            continue
        # get bounding box location
        x,y,w,h = cv2.boundingRect(ctr)
        # draw bounding box around object
        cv2.rectangle(img, (x,y), (x+w, y+h), (204,119,0), 2)
        # get canny image
        cv2.imwrite('detection_object_contour.jpg', canny)
        # get marked image
        cv2.imwrite('detection_bounding_box.jpg', img)

        # display detection contour in frontend
        detection_contour = QImage('detection_object_contour.jpg')
        detection_contour_map = QPixmap.fromImage(detection_contour)
        self.detection_contour.setPixmap(detection_contour_map)
        # display detection bounding box in frontend
        detection_image = QImage('detection_bounding_box.jpg')
        detection_image_map = QPixmap.fromImage(detection_image)
        self.detection.setPixmap(detection_image_map)
                
    # also show live video for reference
    cv2.imshow(RTSP_URL, img)

    if cv2.waitKey(1) == 27:  # Keep running until you press `esc`
        break

cap.release()
cv2.destroyAllWindows()

INSTAR IP Camera Motion Detector