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• DNN OpenCV Python using RSTP always crash after few minutes

  1er juillet 2022, par renaldyks

  Description :

  


  I want to create a people counter using DNN. The model I'm using is MobileNetSSD. The camera I use is IPCam from Hikvision. Python communicates with IPCam using the RSTP protocol.

  


  The program that I made is good and there are no bugs, when running the sample video the program does its job well. But when I replaced it with IPcam there was an unknown error.

  


  Error :

  


  Sometimes the error is :

  


  [h264 @ 000001949f7adfc0] error while decoding MB 13 4, bytestream -6
[h264 @ 000001949f825ac0] left block unavailable for requested intra4x4 mode -1
[h264 @ 000001949f825ac0] error while decoding MB 0 17, bytestream 762


  


  Sometimes the error does not appear and the program is killed.

  


  ---

  


  Update Error

  


  After revising the code, I caught the error. The error found is

  


  [h264 @ 0000019289b3fa80] error while decoding MB 4 5, bytestream -25


  


  Now I don't know what to do, because the error is not in Google.

  


  Source Code :

  


  Old Code

  


  This is my very earliest code before getting suggestions from the comments field.

  


  import time
import cv2
import numpy as np
import math
import threading

print("Load MobileNeteSSD model")

prototxt = "MobileNetSSD_deploy.prototxt"
model = "MobileNetSSD_deploy.caffemodel"

CLASSES = ["background", "aeroplane", "bicycle", "bird", "boat",
           "bottle", "bus", "car", "cat", "chair", "cow", "diningtable",
           "dog", "horse", "motorbike", "person", "pottedplant", "sheep",
           "sofa", "train", "tvmonitor"]

net = cv2.dnn.readNetFromCaffe(prototxt, model)

pos_line = 0
offset = 50
car = 0
detected = False
check = 0
prev_frame_time = 0


def detect():
    global check, car, detected
    check = 0
    if(detected == False):
        car += 1
        detected = True


def center_object(x, y, w, h):
    cx = x + int(w / 2)
    cy = y + int(h / 2)
    return cx, cy


def process_frame_MobileNetSSD(next_frame):
    global car, check, detected

    rgb = cv2.cvtColor(next_frame, cv2.COLOR_BGR2RGB)
    (H, W) = next_frame.shape[:2]

    blob = cv2.dnn.blobFromImage(next_frame, size=(300, 300), ddepth=cv2.CV_8U)
    net.setInput(blob, scalefactor=1.0/127.5, mean=[127.5, 127.5, 127.5])
    detections = net.forward()

    for i in np.arange(0, detections.shape[2]):
        confidence = detections[0, 0, i, 2]

        if confidence > 0.5:

            idx = int(detections[0, 0, i, 1])
            if CLASSES[idx] != "person":
                continue

            label = CLASSES[idx]

            box = detections[0, 0, i, 3:7] * np.array([W, H, W, H])
            (startX, startY, endX, endY) = box.astype("int")

            center_ob = center_object(startX, startY, endX-startX, endY-startY)
            cv2.circle(next_frame, center_ob, 4, (0, 0, 255), -1)

            if center_ob[0] < (pos_line+offset) and center_ob[0] > (pos_line-offset):
                # car+=1
                detect()

            else:
                check += 1
                if(check >= 5):
                    detected = False

            cv2.putText(next_frame, label+' '+str(round(confidence, 2)),
                        (startX, startY-10), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
            cv2.rectangle(next_frame, (startX, startY),
                          (endX, endY), (0, 255, 0), 3)

    return next_frame


def PersonDetection_UsingMobileNetSSD():
    cap = cv2.VideoCapture()
    cap.open("rtsp://admin:Admin12345@192.168.100.20:554/Streaming/channels/2/")

    global car,pos_line,prev_frame_time

    frame_count = 0

    while True:
        try:
            time.sleep(0.1)
            new_frame_time = time.time()
            fps = int(1/(new_frame_time-prev_frame_time))
            prev_frame_time = new_frame_time

            ret, next_frame = cap.read()
            w_video = cap.get(cv2.CAP_PROP_FRAME_WIDTH)
            h_video = cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
            pos_line = int(h_video/2)-50

            if ret == False: break

            frame_count += 1
            cv2.line(next_frame, (int(h_video/2), 0),
                     (int(h_video/2), int(h_video)), (255, 127, 0), 3)
            next_frame = process_frame_MobileNetSSD(next_frame)

            cv2.rectangle(next_frame, (248,22), (342,8), (0,0,0), -1)
            cv2.putText(next_frame, "Counter : "+str(car), (250, 20),
                        cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 1)
            cv2.putText(next_frame, "FPS : "+str(fps), (0, int(h_video)-10),
                        cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 1)
            cv2.imshow("Video Original", next_frame)
            # print(car)

        except Exception as e:
            print(str(e))

        if cv2.waitKey(1) & 0xFF == ord('q'): 
            break


    print("/MobileNetSSD Person Detector")


    cap.release()
    cv2.destroyAllWindows()

if __name__ == "__main__":
    t1 = threading.Thread(PersonDetection_UsingMobileNetSSD())
    t1.start()


  


  New Code

  


  I have revised my code and the program still stops taking frames. I just revised the PersonDetection_UsingMobileNetSSD() function. I've also removed the multithreading I was using. The code has been running for about 30 minutes but after a broken frame, the code will never re-execute the program block if ret == True.

  


  def PersonDetection_UsingMobileNetSSD():
    cap = cv2.VideoCapture()
    cap.open("rtsp://admin:Admin12345@192.168.100.20:554/Streaming/channels/2/")

    global car,pos_line,prev_frame_time

    frame_count = 0

    while True:
        try:
            if cap.isOpened():
                ret, next_frame = cap.read()
                if ret:
                    new_frame_time = time.time()
                    fps = int(1/(new_frame_time-prev_frame_time))
                    prev_frame_time = new_frame_time
                    w_video = cap.get(cv2.CAP_PROP_FRAME_WIDTH)
                    h_video = cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
                    pos_line = int(h_video/2)-50

                    # next_frame = cv2.resize(next_frame,(720,480),fx=0,fy=0, interpolation = cv2.INTER_CUBIC)

                    if ret == False: break

                    frame_count += 1
                    cv2.line(next_frame, (int(h_video/2), 0),
                            (int(h_video/2), int(h_video)), (255, 127, 0), 3)
                    next_frame = process_frame_MobileNetSSD(next_frame)

                    cv2.rectangle(next_frame, (248,22), (342,8), (0,0,0), -1)
                    cv2.putText(next_frame, "Counter : "+str(car), (250, 20),
                                cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 1)
                    cv2.putText(next_frame, "FPS : "+str(fps), (0, int(h_video)-10),
                                cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 1)
                    cv2.imshow("Video Original", next_frame)
                    # print(car)
                else:
                    print("Crashed Frame")
            else:
                print("Cap is not open")

        except Exception as e:
            print(str(e))

        if cv2.waitKey(1) & 0xFF == ord('q'): 
            break


    print("/MobileNetSSD Person Detector")


    cap.release()
    cv2.destroyAllWindows()


  


  Requirement :

  


  Hardware : Intel i5-1035G1, RAM 8 GB, NVIDIA GeForce MX330

  


  Software : Python 3.6.2 , OpenCV 4.5.1, Numpy 1.16.0

  


  Question :

  


  

  1. What should i do for fixing this error ?

  


  2. What causes this to happen ?

  


  


  Best Regards,

  


  ---

  


  Thanks

  


• Combining Opencv Raw frames with Microphone Audio stream Using ffmpeg

  10 août 2022, par Abhishek Vats

  I am trying to build a sports analysis platform where I have a deep learning model which processes Live video(RTMP/Webcam) frames, applies overlays,score etc. and then I need to combine it with microphone audio and rebroadcast with audio and video in sync. I think I need the presentation time stamps of the frames (Since AI frame processing takes variable time) and somehow provide ffmpeg with it but I'm lost and could not find a similar example doing this.

  


• Way to bypass video upload when testing using Rspec

  1er mars 2014, par Justin

  I'm testing a page on my app that shows videos. I'm trying to speed up the test by bypassing the video upload process or another way ??

  Maybe I'm using FactoryGirl incorrectly for file uploads..

  Using FactoryGirl, I'm creating the video with

  FactoryGirl.define do
  
   factory :video do
  
    user_id 1
  
    type "Live"
  
    title "FooBar"
  
    description "Foo bar is the description"
  
    video { fixture_file_upload(Rails.root.join('spec', 'files', 'concert.mov'), 'video/mp4') }
  
   end
  
  end

  And in the request's spec I'm describing the videos as :

  describe "videos page" do
  
  
  
    let(:user) { FactoryGirl.create(:user) }
  
    let!(:video1) { FactoryGirl.create(:video) }
  
  
  
    before { visit user_video_path(user) }
  
  
  
    it { should have_title(user.name) }
  
    it { should have_content(user.name) }
  
  
  
    describe "videos" do
  
      it { should have_content(video1.description) }
  
    end
  
  end

  Now, everytime I run the test for this page it goes through the file upload process which takes more time. I'm also using FFmpeg

  **video.rb (video model)**
  
  
  
  validates :video, presence: true
  
  has_attached_file :video, :styles => {
  
                                        :medium => { :geometry => "640x480", :format => 'mp4' },
  
                                        :thumb => { :geometry => "470x290#", :format => 'jpg', :time => 10 }
  
                                       }, 
  
                            :processors => [:ffmpeg]

  What this does when I test the page is the CLI goes through the video upload process like it would if you were uploading the video and watching your local server.