identifying moving objects opencv

CV2 Import 
Import Time 
Import datetime 
Import os 


DEF mkdir (path): 
    Folder = os.path.exists (path) 

    IF not Folder: # determine whether there is a folder if not exist, create the folder 
        os.makedirs (path) # makedirs when you create a file path will be created if this path does not exist 
        Print 
        ( "new new Folder ... --- ---") 
        Print 
        ( "the OK --- ---") 

    the else: 
        Print 
        ( "--- There IS the this --- Folder ")! 


file =" D: \\ CCTVlook "save location # 
mkdir (file) 
Print (" files are stored in the D: \\ CCTVlook ") 
# selected camera, notebook 0 built-in camera, 1,2 ??? for the external camera 
camera = cv2.VideoCapture (0) 

Time.sleep (5) # delay 5s perform 
background = None # initialization BACKGROUND

 
def nothing (x):
    Pass 


cv2.namedWindow ( "FPS") # Create a window 
cv2.createTrackbar ( "level", "fps ", 21, 255, nothing) # Create a threshold slider 
shot_idx = 0 

the while True: 
    text = "No the Target" 
    Flat = 0 
    # slider assignment 
    kerne = cv2.getTrackbarPos ( "Level", "FPS") 
    IF kerne% 2 == 0: 
        kerne. 1 = # + kerne slider solution Gaussian filter is an even number assigned to an exception is thrown 
    (grabbed, frame ) = camera.read () 
    # frame preprocessing, the first grayscale, then the Gaussian filter. 
    # Gaussian filtering on the image processing parameters to avoid small changes in brightness, vibration and the like affect the results 
    Gray = cv2.cvtColor (Frame, cv2.COLOR_BGR2GRAY) 
    Gray = cv2.GaussianBlur (Gray, (kerne, kerne), 0) 
    # of the first background of the entire frame is set as the input 
    if background is None:
    = cv2.absdiff frameDelta (background, Gray) 
    # binarized 
    Thresh = cv2.threshold (frameDelta, 25, 255, cv2.THRESH_BINARY) [. 1] 
    # erosion and dilation 
    thresh = cv2.dilate (thresh, None, iterations = 2) 
    # fetch contour 
    CNTs = cv2.findContours (thresh.copy (), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) [ 
        -2 
    ] 
    # traverse profile 
    for CNTs in C: 
        IF cv2.contourArea (C) <1800: for smaller rectangle # region, choose to ignore 
            Continue 
        Flat set # 1 = a tag, when there is a movement 
        # calculated contour bounding box, the box is drawn in the current frame 
        (x, y, w, h ) = cv2.boundingRect (c)
        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 2)
        text = "Find Target! save as D:\CCTVlook"
        print("Find Target!")
    cv2.putText(frame, 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,
    )
    # cv2.imshow("Frame Delta", frameDelta)

    cv2.imshow("fps", frame)
    # cv2.imshow("Thresh", thresh)

    key = cv2.waitKey(1) &0xFF 

    # If the q key has been pressed out of the loop
    ch = cv2.waitKey(1)
    if key == ord("q"):
        break

    if flat == 1:  # 设置一个标签，当有运动的时候为1
        fn = "D:\CCTVlook\shot%d.jpg" % (shot_idx)
        cv2.imwrite(fn, frame)
        shot_idx += 1
        continue

　　Original: https://blog.csdn.net/dgut_guangdian/article/details/79762409