Python calls OpenCV to implement camera motion detection [Raspberry Pi]

[Hardware Environment]

Raspberrypi 3-Generation B (UK version)

[Software Environment]

Operating system: Raspbian

Python version: 2.7.3

Python Library:

1.1) Opencv-python (3.2.0.6)

[Construction process]

OpenCV Python Library:

1. PIP Installation

[The relevant code (temporarily unverified, removed from the author's original code in the Dropbox Automatic upload section)]

pi_surveillance.py

#USAGE#python pi_surveillance.py--conf Conf.json#Import the necessary packages fromPyimagesearch.tempimageImportTempimage fromPicamera.arrayImportPirgbarray#Picamera (CANT be imported on WINDOWS PLATFORM) fromPicameraImportPicamera#Picamera (CANT be imported on WINDOWS PLATFORM)ImportArgparseImportWarningsImportdatetimeImportimutilsImportJSONImport TimeImportCv2#construct the argument parser and the parse the argumentsAP =Argparse. Argumentparser () ap.add_argument ("- C","--conf", Required=true, help="path to the JSON configuration file") args=VARs (Ap.parse_args ())#filter warnings, load the configuration and initialize the DropboxClientWarnings.filterwarnings ("Ignore") Conf= Json.load (Open (args["conf"])) client=None#initialize the camera and grab a reference to the raw camera captureCamera =Picamera () camera.resolution= Tuple (conf["resolution"]) Camera.framerate= conf["fps"]rawcapture= Pirgbarray (Camera, Size=tuple (conf["resolution"]))#Allow the camera to warmup, then initialize the average frame, last#uploaded timestamp, and frame motion counterPrint "[INFO] warming up ..."Time.sleep (conf["Camera_warmup_time"]) Avg=nonelastuploaded=Datetime.datetime.now () motioncounter=0#capture Frames from the camera forFinchCamera.capture_continuous (Rawcapture, format="BGR", use_video_port=True):#grab the raw NumPy array representing the image and initialize    #The timestamp and occupied/unoccupied textframe =F.array Timestamp=datetime.datetime.now () text="unoccupied"    #Resize the frame, convert it to grayscale, and blur itframe = Imutils.resize (frame, width=500) Gray=Cv2.cvtcolor (frame, cv2. Color_bgr2gray) Gray= Cv2. Gaussianblur (Gray, (21, 21), 0)#If the average frame is None, initialize it    ifAvg isNone:Print "[INFO] Starting background model ..."avg= Gray.copy (). Astype ("float") rawcapture.truncate (0)Continue    #accumulate the weighted average between the current frame and    #previous frames, then compute the difference between the current    #frame and running averageCv2.accumulateweighted (Gray, AVG, 0.5) Framedelta=Cv2.absdiff (Gray, Cv2.convertscaleabs (avg))#threshold The delta image, dilate the thresholded image to fill    #in holes, then find contours on thresholded imageThresh = Cv2.threshold (Framedelta, conf["Delta_thresh"], 255, Cv2. thresh_binary) [1] Thresh= Cv2.dilate (Thresh, None, iterations=2) (CNTs, _)=cv2.findcontours (Thresh.copy (), Cv2. Retr_external, Cv2. Chain_approx_simple)#Loop over the contours     forCinchCNTs:#if the contour is too small, ignore it        ifCv2.contourarea (c) < conf["Min_area"]:            Continue        #compute the bounding box for the contour, draw it on the frame,        #and update the text(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 frameTS = Timestamp.strftime ("%A%d%B%Y%i:%m:%s%p") Cv2.puttext (frame,"The Status: {}". Format (text), (10, 20), Cv2. Font_hershey_simplex,0.5, (0, 0, 255), 2) Cv2.puttext (frame, TS, (Ten, Frame.shape[0]-10), Cv2. Font_hershey_simplex,0.35, (0, 0, 255), 1)    #check to see if the occupied    ifText = ="occupied":        #Check to see if enough time have passed between uploads        if(timestamp-lastuploaded). Seconds >= conf["Min_upload_seconds"]:            #Increment the motion counterMotioncounter + = 1#Check to see if the number of frames with consistent motion is            #High enough            ifMotioncounter >= conf["Min_motion_frames"]:                #Check to see if Dropbox sohuld is used                ifconf["Use_dropbox"]:                    #write the image to temporary filet =tempimage () cv2.imwrite (T.path, frame)#upload the image to Dropbox and cleanup the tempory image                    Print "[UPLOAD] {}". Format (TS) path="{base_path}/{timestamp}.jpg". Format (Base_path=conf["Dropbox_base_path"], timestamp=ts) client.put_file (path, open (T.path,"RB") ) T.cleanup ()#update the last uploaded timestamp and reset the motion                #counterlastuploaded =timestamp Motioncounter=0#Otherwise, the hostel is not occupied    Else: Motioncounter=0#Check to see if the frames should is displayed to screen    ifconf["Show_video"]:        #Display the security feedCv2.imshow ("Security Feed", frame) key= Cv2.waitkey (1) & 0xFF#if the ' Q ' key is pressed, break from the Lop        ifKey = = Ord ("Q"):             Break    #clear the stream in preparation for the next frameRawcapture.truncate (0)

Conf.json

{    "Show_video": True,    "Use_dropbox": True,    "Dropbox_key": "Your_dropbox_key",    "Dropbox_secret": " Your_dropbox_secret ",    " Dropbox_base_path ":" Your_dropbox_app_path ",    " Min_upload_seconds ": 3.0,    " min _motion_frames ": 8,    " Camera_warmup_time ": 2.5,    " Delta_thresh ": 5,    " Resolution ": [640, 480],    " FPS ": +,    " Min_area ": 5000}

tempimage.py

#Import the necessary packagesImportUUIDImportOSclassTempimage:def __init__(Self, basepath="./", ext=". jpg"):        #construct the file pathSelf.path ="{Base_path}/{rand}{ext}". Format (base_path=BasePath, Rand=str (Uuid.uuid4 ()), ext=ext)defCleanup (self):#Remove the fileOs.remove (Self.path)

Python calls OpenCV to implement camera motion detection [Raspberry Pi]