def insertVideo(): try: if session['loginRole'] == 'admin': videoVO = VideoVO() videoDAO = VideoDAO() UPLOAD_FOLDER = 'C:/project/admin/project/static/adminResources/video' app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER file = request.files['videoFile'] filename = secure_filename(file.filename) filepath = os.path.join(app.config['UPLOAD_FOLDER']) file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename)) videoVO.videoFilename = filename print videoVO.videoFilename videoVO.videoFilepath = filepath videoVO.videoTitle = request.form['videoTitle'] videoVO.videoDescription = request.form['videoDescription'] videoVO.videoDate, videoVO.videoTime = str( datetime.now()).split(' ') videoVO.videoActiveStatus = 'active' videoDAO.insertVideo(videoVO) return render_template('admin/addVideos.html') else: return render_template('admin/login.html') except: return render_template('admin/login.html')
def adminAjaxGetGraphData(): videoVO = VideoVO() videoDAO = VideoDAO() index_VideoId = request.args.get('index_VideoId') videoVO.videoId = index_VideoId ajaxGraphDataList = videoDAO.ajaxGetGraphData(videoVO) print("ajaxGraphDataList >>>>>>>>>>>>>>>>>> ", ajaxGraphDataList) graphDict = {} counter = False if len(ajaxGraphDataList) != 0: counter = True dict1 = {} for i in ajaxGraphDataList: dict1['illegalCarCount'] = i.illegalCarCount dict1['legalCarCount'] = i.legalCarCount graphDict.update(dict1) print('graphDict>>>', graphDict) if counter: response = {'responseKey': graphDict} print('response>>>>>>>>', response) else: response = {'responseKey': 'Error'} return jsonify(response)
def userDeleteVideo(): try: if adminLoginSession() == 'user': videoVO = VideoVO() videoDAO = VideoDAO() videoId = request.args.get( 'videoId' ) videoVO.videoId = videoId videoVOList = videoDAO.deleteVideo( videoVO ) videoInputFileName = videoVOList.videoInputFileName videoInputFilePath = videoVOList.videoInputFilePath videoOutputFileName = videoVOList.videoOutputFileName videoOutputFilePath = videoVOList.videoOutputFilePath if videoInputFileName is not None: path = videoInputFilePath.replace( '..', 'project' ) + videoInputFileName os.remove( path ) if videoOutputFileName is not None: path = videoOutputFilePath.replace( '..', 'project' ) + videoOutputFileName os.remove( path ) return redirect( url_for( 'userViewVideo' ) ) else: return adminLogoutSession() except Exception as ex: print( ex )
def loadIndex(): try: if session['loginRole'] == 'admin': registerDAO = RegisterDAO() datasetDAO = DatasetDAO() blogDAO = BlogDAO() videoDAO = VideoDAO() complaintDAO = ComplaintDAO() feedbackDAO = FeedbackDAO() predictDAO = PredictDAO() userdict = registerDAO.countuser() companydict = datasetDAO.countcompany() blogDict = blogDAO.countBlog() videoDict = videoDAO.countVideo() complaintDict = complaintDAO.countComplaint() feedbackDict = feedbackDAO.countfeedback() predictDict = predictDAO.searchDPrediction() return render_template('admin/index.html', userdict=userdict, companydict=companydict, blogDict=blogDict, videoDict=videoDict, feedbackDict=feedbackDict, complaintDict=complaintDict, predictDict=predictDict) else: blogDAO = BlogDAO() blogDict = blogDAO.searchBlog() return render_template('user/index.html', blogDict=blogDict) except: return render_template('admin/login.html')
def userDeleteVideo(): try: if adminLoginSession() == 'user': videoVO = VideoVO() videoDAO = VideoDAO() videoId = request.args.get('videoId') videoVO.videoId = videoId videoVOList = videoDAO.deleteVideo(videoVO) inputPath = videoVOList.inputVideoFilePath.replace( '..', 'project') + videoVOList.inputVideoFilename outputPath = videoVOList.outputVideoFilePath.replace( '..', 'project') + videoVOList.outputVideoFilename try: os.remove(inputPath) os.remove(outputPath) except Exception as ex: print(ex) return redirect(url_for('userViewVideo')) else: adminLogoutSession() except Exception as ex: print(ex)
def adminAjaxLoadDateRegister(): videoVO = VideoVO() videoDAO = VideoDAO() index_LoginId = request.args.get('index_LoginId') videoVO.video_LoginId = index_LoginId ajaxAdminIndexDateVOList = videoDAO.ajaxDateAdminIndex(videoVO) print("ajaxAdminIndexDateVOList >>>>>>>>>>>>>>>>>> ", ajaxAdminIndexDateVOList) ajaxDateDictList = [i.as_dict() for i in ajaxAdminIndexDateVOList] print("ajaxDateDictList >>>>>>>>>>>>>>>>>> ", ajaxDateDictList) ajaxAdminIndexDateList = [] for i in ajaxDateDictList: ajaxAdminIndexDateList.append({ "videoId": i['videoId'], "uploadDate": i['uploadDate'].strftime('%d/%m/%Y') }) print("ajaxAdminIndexDateList >>>>>>>>>>>>>>>>>> ", ajaxAdminIndexDateList) return jsonify(ajaxAdminIndexDateList)
def userLoadVideo(): try: if adminLoginSession() == 'user': videoDAO = VideoDAO() videoVOList = videoDAO.viewLocalData() purchaseVO = PurchaseVO() purchaseDAO = PurchaseDAO() purchaseVO.purchase_loginId = session['session_LoginId'] purchaseVOList = purchaseDAO.viewUserPurchase(purchaseVO) purchaseVODict = [[i[0].as_dict(), i[1].as_dict()] for i in [j for j in purchaseVOList]] purchaseDate = [i[0]['purchaseDate'] for i in purchaseVODict] if len(purchaseDate) > 0: dateMax = max(purchaseDate) index = purchaseDate.index(dateMax) purchaseDuration = purchaseVODict[index][1]['packageDuration'] purchaseDuration, _ = purchaseDuration.split(' ') currentDate = date.today() dateDifference = currentDate - dateMax if int(purchaseDuration) * 28 > int(dateDifference.days): return render_template('user/addVideo.html', videoVOList=videoVOList) else: return redirect( url_for( 'userLoadPurchase', msg= 'Current Package Is Expired, Purchase Package To Continue using System' )) else: adminLogoutSession() except Exception as ex: print(ex)
def adminViewVideo(): try: if adminLoginSession() == 'admin': videoDAO = VideoDAO() videoVOList = videoDAO.adminViewVideo() return render_template('admin/viewVideo.html', videoVOList=videoVOList) else: adminLogoutSession() except Exception as ex: print(ex)
def userViewVideo(): try: if adminLoginSession() == 'user': videoVO = VideoVO() videoDAO = VideoDAO() videoVO.video_LoginId = session['session_loginId'] videoVOList = videoDAO.viewVideo( videoVO ) return render_template( 'user/viewVideo.html', videoVOList=videoVOList ) else: return adminLogoutSession() except Exception as ex: print( ex )
def deleteVideo(): try: if session['loginRole'] == 'admin': videoVO = VideoVO() videoDAO = VideoDAO() videoVO.videoId = request.args.get('videoId') videoVO.videoActiveStatus = 'deactive' videoDAO.deleteVideo(videoVO) return redirect(url_for('viewVideo')) else: return render_template('admin/login.html') except: return render_template('admin/login.html')
def userinsertVideo(): try: if adminLoginSession() == 'user': videoVO = VideoVO() videoDAO = VideoDAO() videoType = request.form['videoType'] video_LoginId = session['session_loginId'] file = request.files['file'] print(file) videoFileName = secure_filename(file.filename) print(videoFileName) videoFilePath = os.path.join(app.config['UPLOAD_FOLDER']) print(videoFilePath) file.save(os.path.join(videoFilePath, videoFileName)) videoUploadDate = datetime.date(datetime.now()) videoUploadTime = datetime.time(datetime.now()) videoVO.videoType = videoType videoVO.videoFileName = videoFileName videoVO.videoFilePath = videoFilePath.replace("project", "..") videoVO.videoUploadDate = videoUploadDate videoVO.videoUploadTime = videoUploadTime videoVO.video_LoginId = video_LoginId videoDAO.userInsertVideo(videoVO) return redirect(url_for('userviewVideo')) else: return adminLogoutSession() except Exception as ex: print(ex)
def userInsertVideo(): try: if adminLoginSession() == 'user': inputvideoFilename = request.args.get('videoFilename') inputvideoFilepath = request.args.get('videoFilepath') video_data = request.args.get('video_data') outputvideoFilename = request.args.get('outputVideoFilename') outputvideoFilePath = request.args.get('outputFolder') totalIllegalCarCount = request.args.get('totalIllegalCarCount') totalLegalCarCount = request.args.get('totalLegalCarCount') videoVO = VideoVO() videoDAO = VideoDAO() # saving filename in database todayDate = date.today() # saving current date in database nowTime = datetime.now() # saving current date in database inputvideoFilepath = inputvideoFilepath.replace( "project", "..") # saving filepath in database outputvideoFilePath = outputvideoFilePath.replace("project", "..") videoVO.video_CameraId = video_data.split(',')[0] videoVO.video_CrossroadId = video_data.split(',')[1] videoVO.video_AreaId = video_data.split(',')[2] videoVO.video_LoginId = session['session_LoginId'] videoVO.inputVideoFilename = inputvideoFilename videoVO.inputVideoFilePath = str(inputvideoFilepath) videoVO.uploadTime = nowTime.strftime("%H:%M:%S") videoVO.uploadDate = todayDate videoVO.outputVideoFilename = outputvideoFilename videoVO.outputVideoFilePath = outputvideoFilePath videoVO.illegalCarCount = totalIllegalCarCount videoVO.legalCarCount = totalLegalCarCount videoDAO.insertVideo(videoVO) return redirect(url_for('userViewVideo')) else: adminLogoutSession() except Exception as ex: print(ex)
def viewVideo(): try: if session['loginRole'] == 'admin': videoDAO = VideoDAO() videoDict = videoDAO.searchVideo() return render_template('admin/viewVideo.html', videoDict=videoDict) else: videoDAO = VideoDAO() videoDict = videoDAO.searchVideo() return render_template('user/viewVideos.html', videoDict=videoDict) except: return render_template('admin/login.html')
def adminviewVideo(): try: if adminLoginSession() == 'admin': videoDAO = VideoDAO() videoVO = VideoDAO() video_RegisterId = session['session_registerId'] videoVO.video_RegisterId = video_RegisterId videoVOList = videoDAO.adminViewRegister() print("____________", videoVOList) return render_template('admin/viewVideo.html', videoVOList=videoVOList) else: return adminLogoutSession() except Exception as ex: print(ex)
def userInsertVideo(): try: if adminLoginSession() == 'user': videoVO = VideoVO() videoDAO = VideoDAO() uploadDate = str(datetime.now().date()) uploadTime = datetime.now().strftime('%H:%M:%S') random_number = random.randint(1, 1000) videoOutputFileName = "output_" + str(random_number) + ".webm" videoOutputFilePath = app.config['UPLOAD_FOLDER'] outputVideo = videoOutputFilePath + videoOutputFileName capture = cv2.VideoCapture( r"F:\projectworkspace\project\static\adminResources\inputVideo\input_1.mp4" ) fourcc = cv2.VideoWriter_fourcc(*'VP80') out = cv2.VideoWriter(outputVideo, fourcc, capture_duration, (640, 480)) # Create two opencv named windows cv2.namedWindow("base-image", cv2.WINDOW_AUTOSIZE) cv2.namedWindow("result-image", cv2.WINDOW_AUTOSIZE) # Position the windows next to eachother cv2.moveWindow("base-image", 0, 100) cv2.moveWindow("result-image", 400, 100) # Start the window thread for the two windows we are using cv2.startWindowThread() # The color of the rectangle we draw around the face rectangleColor = (0, 165, 255) # variables holding the current frame number and the current faceid frameCounter = 0 currentFaceID = 0 # Variables holding the correlation trackers and the name per faceid faceTrackers = {} faceNames = {} try: while True: # Retrieve the latest image from the webcam rc, fullSizeBaseImage = capture.read() # Resize the image to 320x240 baseImage = cv2.resize(fullSizeBaseImage, (320, 240)) # Result image is the image we will show the user, which is a # combination of the original image from the webcam and the # overlayed rectangle for the largest face resultImage = baseImage.copy() # STEPS: # * Update # # # all trackers and remove the ones that are not # relevant anymore # * Every 10 frames: # + Use face detection on the current frame and look # for faces. # + For each found face, check if centerpoint is within # existing tracked box. If so, nothing to do # + If centerpoint is NOT in existing tracked box, then # we add a new tracker with a new face-id # Increase the framecounter frameCounter += 1 # Update all the trackers and remove the ones for which the update # indicated the quality was not good enough fidsToDelete = [] for fid in faceTrackers.keys(): trackingQuality = faceTrackers[fid].update(baseImage) # If the tracking quality is good enough, we must delete # this tracker if trackingQuality < 7: fidsToDelete.append(fid) for fid in fidsToDelete: print("Removing fid " + str(fid) + " from list of trackers") faceTrackers.pop(fid, None) # Every 10 frames, we will have to determine which faces # are present in the frame if (frameCounter % 10) == 0: # For the face detection, we need to make use of a gray # colored image so we will convert the baseImage to a # gray-based image gray = cv2.cvtColor(baseImage, cv2.COLOR_BGR2GRAY) # Now use the haar cascade detector to find all faces # in the image faces = faceCascade.detectMultiScale(gray, 1.3, 5) # Loop over all faces and check if the area for this # face is the largest so far # We need to convert it to int here because of the # requirement of the dlib tracker. If we omit the cast to # int here, you will get cast errors since the detector # returns numpy.int32 and the tracker requires an int matchedFid = None for (_x, _y, _w, _h) in faces: x = int(_x) y = int(_y) w = int(_w) h = int(_h) # calculate the centerpoint x_bar = x + 0.5 * w y_bar = y + 0.5 * h # Variable holding information which faceid we # matched with # Now loop over all the trackers and check if the # centerpoint of the face is within the box of a # tracker for fid in faceTrackers.keys(): tracked_position = faceTrackers[ fid].get_position() t_x = int(tracked_position.left()) t_y = int(tracked_position.top()) t_w = int(tracked_position.width()) t_h = int(tracked_position.height()) # calculate the centerpoint t_x_bar = t_x + 0.5 * t_w t_y_bar = t_y + 0.5 * t_h # check if the centerpoint of the face is within the # rectangleof a tracker region. Also, the centerpoint # of the tracker region must be within the region # detected as a face. If both of these conditions hold # we have a match if ((t_x <= x_bar <= (t_x + t_w)) and (t_y <= y_bar <= (t_y + t_h)) and (x <= t_x_bar <= (x + w)) and (y <= t_y_bar <= (y + h))): matchedFid = fid # If no matched fid, then we have to create a new tracker if matchedFid is None: print("Creating new tracker " + str(currentFaceID)) start_time = time.time() minutes = 0 # Create and store the tracker tracker = dlib.correlation_tracker() tracker.start_track( baseImage, dlib.rectangle(x - 10, y - 20, x + w + 10, y + h + 20)) faceTrackers[currentFaceID] = tracker # Start a new thread that is used to simulate # face recognition. This is not yet implemented in this # version :) t = threading.Thread(target=doRecognizePerson, args=(faceNames, currentFaceID)) t.start() # Increase the currentFaceID counter currentFaceID += 1 # Now loop over all the trackers we have and draw the rectangle # around the detected faces. If we 'know' the name for this person # (i.e. the recognition thread is finished), we print the name # of the person, otherwise the message indicating we are detecting # the name of the person for fid in faceTrackers.keys(): tracked_position = faceTrackers[fid].get_position() t_x = int(tracked_position.left()) t_y = int(tracked_position.top()) t_w = int(tracked_position.width()) t_h = int(tracked_position.height()) cv2.rectangle(resultImage, (t_x, t_y), (t_x + t_w, t_y + t_h), rectangleColor, 2) if fid in faceNames.keys(): cv2.putText(resultImage, faceNames[fid], (int(t_x + t_w / 2), int(t_y)), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 2) else: cv2.putText(resultImage, "Detecting...", (int(t_x + t_w / 2), int(t_y)), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 2) for fid in faceTrackers.keys(): print("fid>>>>>>>", fid) ffid = faceTrackers[fid] seconds = int(time.time() - start_time) - minutes * 60 print(seconds) if ffid is not None and seconds == capture_duration: print(seconds) sender = "*****@*****.**" receiver = session['session_loginUsername'] currentDate = datetime.now().date() currentTime = datetime.now().strftime( '%H:%M:%S') body = 'Your child is watching t.v continue: \nDate:{}\nTime:{}'.format( currentDate, currentTime) msg = MIMEMultipart() msg['From'] = sender msg['To'] = receiver msg['Subject'] = "DETECTION" msg.attach(MIMEText(body, 'plain')) # To change the payload into encoded form server = smtplib.SMTP('smtp.gmail.com', 587) server.starttls() server.login(sender, "qazwsxedcrfvtgb1234567890") text = msg.as_string() server.sendmail(sender, receiver, text) server.quit() break # Since we want to show something larger on the screen than the # original 320x240, we resize the image again # # Note that it would also be possible to keep the large version # of the baseimage and make the result image a copy of this large # base image and use the scaling factor to draw the rectangle # at the right coordinates. largeResult = cv2.resize(resultImage, (640, 480), interpolation=cv2.INTER_AREA) out.write(largeResult) # Finally, we want to show the images on the screen cv2.imshow("base-image", baseImage) cv2.imshow("result-image", largeResult) # Check if a key was pressed and if it was Q, then break # from the infinite loop pressedKey = cv2.waitKey(2) if pressedKey == ord('q'): break capture.release() out.release() cv2.destroyAllWindows() # To ensure we can also deal with the user pressing Ctrl-C in the console # we have to check for the KeyboardInterrupt exception and break out of # the main loop except KeyboardInterrupt as e: pass videoVO.videoOutputFileName = videoOutputFileName videoVO.videoOutputFilePath = videoOutputFilePath.replace( 'project', '..') videoVO.videoUploadDate = uploadDate videoVO.videoUploadTime = uploadTime videoVO.video_LoginId = session['session_loginId'] videoDAO.insertVideo(videoVO) return redirect(url_for('userViewVideo')) else: return adminLogoutSession() except Exception as ex: print(ex)
def userInsertVideo(): try: if adminLoginSession() == 'user': videoVO = VideoVO() videoDAO = VideoDAO() file = request.files['file'] videoInputFileName = secure_filename( file.filename ) videoInputFilePath = os.path.join( app.config['UPLOAD_INPUTVIDEO_FOLDER'] ) file.save( os.path.join( videoInputFilePath, videoInputFileName ) ) inputVideo = videoInputFilePath + videoInputFileName videoOutputFileName = videoInputFileName.replace( '.mp4', '.webm' ) videoOutputFilePath = os.path.join( app.config['UPLOAD_OUTPUTVIDEO_FOLDER'] ) outputVideo = videoOutputFilePath + videoOutputFileName confidence_default = 0.4 skip_frames = 25 s1 = 'project/static/userResource/modelDump/MobileNetSSD_deploy.prototxt' model = 'project/static/userResource/modelDump/MobileNetSSD_deploy.caffemodel' userName = session['session_loginUsername'] print( "userName="******"background", "aeroplane", "bicycle", "bird", "boat", "bottle", "bus", "car", "cat", "chair", "cow", "diningtable", "dog", "horse", "motorbike", "person", "pottedplant", "sheep", "sofa", "train", "tvmonitor"] # load our serialized model from disk print( "[INFO] loading model..." ) net = cv2.dnn.readNetFromCaffe( s1, model ) # print(">>>>>>>>>>>>>>>>>>>>>>>loding") # if a video path was not supplied, grab a reference to the webcam if not inputVideo: print( "[INFO] starting video stream..." ) vs = VideoStream( src=0 ).start() time.sleep( 2.0 ) # otherwise, grab a reference to the video file else: print( "[INFO] opening video file..." ) vs = cv2.VideoCapture( inputVideo ) # initialize the video writer (we'll instantiate later if need be) writer = None # initialize the frame dimensions (we'll set them as soon as we read # the first frame from the video) W = None H = None # instantiate our centroid tracker, then initialize a list to store # each of our dlib correlation trackers, followed by a dictionary to # map each unique object ID to a TrackableObject ct = CentroidTracker( maxDisappeared=40, maxDistance=50 ) trackers = [] trackableObjects = {} # initialize the total number of frames processed thus far, along # with the total number of objects that have moved either up or down totalFrames = 0 miny = 0 # start the frames per second throughput estimator fps = FPS().start() # loop over frames from the video stream while True: # grab the next frame and handle if we are reading from either # VideoCapture or VideoStream frame = vs.read() frame = frame[1] if (inputVideo != False) else frame # if we are viewing a video and we did not grab a frame then we # have reached the end of the video if inputVideo is not None and frame is None: break # resize the frame to have a maximum width of 500 pixels (the # less data we have, the faster we can process it), then convert # the frame from BGR to RGB for dlib frame = imutils.resize( frame, width=500 ) rgb = cv2.cvtColor( frame, cv2.COLOR_BGR2RGB ) # if the frame dimensions are empty, set them if W is None or H is None: (H, W) = frame.shape[:2] # if we are supposed to be writing a video to disk, initialize # the writer if outputVideo is not None and writer is None: fourcc = cv2.VideoWriter_fourcc( *"VP80" ) writer = cv2.VideoWriter( outputVideo, fourcc, 30, (W, H), True ) # initialize the current status along with our list of bounding # box rectangles returned by either (1) our object detector or # (2) the correlation trackers status = "Waiting" rects = [] # check to see if we should run a more computationally expensive # object detection method to aid our tracker if totalFrames % skip_frames == 0: # set the status and initialize our new set of object trackers status = "Detecting" trackers = [] print( "detectiong" ) # convert the frame to a blob and pass the blob through the # network and obtain the detections blob = cv2.dnn.blobFromImage( frame, 0.007843, (W, H), 127.5 ) net.setInput( blob ) detections = net.forward() # loop over the detections for i in np.arange( 0, detections.shape[2] ): # extract the confidence (i.e., probability) associated # with the prediction confidence = detections[0, 0, i, 2] # print("in detectioooon for loop") # filter out weak detections by requiring a minimum # confidence if confidence > confidence_default: # extract the index of the class label from the # detections list idx = int( detections[0, 0, i, 1] ) # if the class label is not a person, ignore it if CLASSES[idx] != "person": print( "detect person" ) continue # compute the (x, y)-coordinates of the bounding box # for the object box = detections[0, 0, i, 3:7] * np.array( [W, H, W, H] ) (startX, startY, endX, endY) = box.astype( "int" ) # construct a dlib rectangle object from the bounding # box coordinates and then start the dlib correlation # tracker tracker = dlib.correlation_tracker() compare.append( (startX, startY) ) for i in compare: if miny < i[1]: miny = i[1] # add the tracker to our list of trackers so we can # utilize it during skip frames rect = dlib.rectangle( int( startX ), int( miny ), int( endX ), int( endY ) ) tracker.start_track( rgb, rect ) trackers.append( tracker ) # otherwise, we should utilize our object *trackers* rather than # object *detectors* to obtain a higher frame processing throughput else: miny = 0 # loop over the trackers for tracker in trackers: # set the status of our system to be 'tracking' rather # than 'waiting' or 'detecting' status = "Tracking" # update the tracker and grab the updated position tracker.update( rgb ) pos = tracker.get_position() # unpack the position object startX = int( pos.left() ) startY = int( pos.top() ) endX = int( pos.right() ) endY = int( pos.bottom() ) # add the bounding box coordinates to the rectangles list compare.append( (startX, startY) ) for i in compare: if miny < i[1]: miny = i[1] rects.append( (startX, miny, endX, endY) ) cv2.rectangle( frame, (startX, miny), (endX, endY), 2 ) # draw a horizontal line in the center of the frame -- once an # object crosses this line we will determine whether they were # moving 'up' or 'down' cv2.line( frame, (int( W // 1.5 ), 0), (int( W // 1.5 ), H), (0, 255, 255), 2 ) cv2.line( frame, (int( W // 2 ), 0), (int( W // 2 ), H), (255, 0, 0), 2 ) cv2.line( frame, (0, int( H // 5 )), (W, int( H // 5 )), (255, 0, 255), 2 ) # use the centroid tracker to associate the (1) old object # centroids with (2) the newly computed object centroids objects = ct.update( rects ) caution = 0 danger = 0 safe = 0 for i in rects: if i[1] < H // 5: continue if W // 3 > i[0] > W // 3: caution += 1 Cautionlist.append( caution ) elif i[0] > W // 3: safe += 1 Safelist.append( safe ) elif i[0] < W // 3: danger += 1 Dangerlist.append( danger ) # loop over the tracked objects for (objectID, centroid) in objects.items(): # check to see if a trackable object exists for the current # object ID to = trackableObjects.get( objectID, None ) trackableObjects[objectID] = to # draw both the ID of the object and the centroid of the # object on the outputVideo frame text = "ID {}".format( objectID ) if len( rects ) == 0: continue cv2.putText( frame, text, (rects[len( rects ) - 1][0] - 10, rects[len( rects ) - 1][1] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2 ) cv2.circle( frame, (rects[len( rects ) - 1][0], rects[len( rects ) - 1][1]), 4, (0, 255, 0), -1 ) # construct a tuple of information we will be displaying on the # frame info = [ ("Danger", danger), ("Caution", caution), ("Safe", safe), ("Status", status), ] for (i, (k, v)) in enumerate( info ): text = "{}: {}".format( k, v ) cv2.putText( frame, text, (10, H - ((i * 20) + 20)), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2 ) # check to see if we should write the frame to disk if writer is not None: writer.write( frame ) cv2.imshow( "Frame", frame ) key = cv2.waitKey( 1 ) & 0xFF if key == ord( "q" ): break totalFrames += 1 fps.update() if len( Dangerlist ) == 2: # song = AudioSegment.from_wav("1.wav") # start = time.time() # the variable that holds the starting time # elapsed = 0 # the variable that holds the number of seconds elapsed. # while elapsed < 10: # while less than 30 seconds have elapsed # play(song) # # elapsed = time.time() - start message = "______DANGER_______Child has touch the grill." fromaddr = "*****@*****.**" toaddr = userName msg = MIMEMultipart() msg['From'] = fromaddr msg['To'] = toaddr msg['Subject'] = "Child Security" msg.attach( MIMEText( message, 'plain' ) ) server = smtplib.SMTP( 'smtp.gmail.com', 587 ) server.starttls() server.login( fromaddr, "9925646618" ) text = msg.as_string() server.sendmail( fromaddr, toaddr, text ) server.quit() print( "frame by camera", totalFrames ) fps.stop() if writer is not None: writer.release() if not inputVideo: vs.stop() else: vs.release() cv2.destroyAllWindows() videoUploadDate = str( datetime.now().date() ) videoUploadTime = datetime.now().strftime( '%H:%M:%S' ) videoVO.videoUploadDate = videoUploadDate videoVO.videoUploadTime = videoUploadTime videoVO.videoInputFileName = videoInputFileName videoVO.videoInputFilePath = videoInputFilePath.replace( 'project', '..' ) videoVO.videoOutputFileName = videoOutputFileName videoVO.videoOutputFilePath = videoOutputFilePath.replace( 'project', '..' ) videoVO.video_LoginId = session['session_loginId'] videoDAO.insertVideo( videoVO ) return redirect( url_for( 'userViewVideo' ) ) else: return adminLogoutSession() except Exception as ex: print( ex )