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• How to solve error : "cvCreateFileCaptureWithPreference : backend FFMPEG doesn't support legacy API anymore"

  24 octobre 2018, par Sarvin

  I am trying to build and run an OpenCV project from Github using OpenCV 3.4.2, Cmake 3.13.0-rc1 and VS 2017. The project builds successfully as I understand from the build output but it throws the above warning after I run the program. The video I want to load is in a .AVI format and uses cvCaptureFromAVI function. Just trying to learn OpenCV, your help and kindness is appreciated.

  Source :

  #include <iostream>
  
  #include <opencv2></opencv2>opencv.hpp>
  
  
  
  #include "package_bgs/PBAS/PixelBasedAdaptiveSegmenter.h"
  
  #include "package_tracking/BlobTracking.h"
  
  #include "package_analysis/VehicleCouting.h"
  
  
  
  using namespace cv;
  
  
  
  int main(int argc, char **argv)
  
  {
  
    std::cout &lt;&lt; "Using OpenCV " &lt;&lt; CV_MAJOR_VERSION &lt;&lt; "." &lt;&lt; 
  
    CV_MINOR_VERSION &lt;&lt; "." &lt;&lt; CV_SUBMINOR_VERSION &lt;&lt; std::endl;
  
  
  
    /* Open video file */
  
    CvCapture *capture = 0;
  
  
  
    capture = cvCaptureFromAVI("video.avi");
  
    if(!capture){
  
      std::cerr &lt;&lt; "Cannot open video ting tong!" &lt;&lt; std::endl;
  
      return 1;
  
    }
  
  
  
    /* Background Subtraction Algorithm */
  
    IBGS *bgs;
  
    bgs = new PixelBasedAdaptiveSegmenter;
  
  
  
    /* Blob Tracking Algorithm */
  
  
  
  
  
  
  
  cv::Mat img_blob;
  
    BlobTracking* blobTracking;
  
    blobTracking = new BlobTracking;
  
  
  
    /* Vehicle Counting Algorithm */
  
    VehicleCouting* vehicleCouting;
  
    vehicleCouting = new VehicleCouting;
  
  
  
    std::cout &lt;&lt; "Press 'q' to quit..." &lt;&lt; std::endl;
  
    int key = 0;
  
    IplImage *frame;
  
    while(key != 'q')
  
    {
  
      frame = cvQueryFrame(capture);
  
      if(!frame) break;
  
  
  
      cv::Mat img_input = cv::cvarrToMat(frame);
  
      cv::imshow("Input", img_input);
  
  
  
      // bgs->process(...) internally process and show the foreground mask image
  
      cv::Mat img_mask;
  
      bgs->process(img_input, img_mask);
  
  
  
      if(!img_mask.empty())
  
      {
  
        // Perform blob tracking
  
        blobTracking->process(img_input, img_mask, img_blob);
  
  
  
        // Perform vehicle counting
  
        vehicleCouting->setInput(img_blob);
  
        vehicleCouting->setTracks(blobTracking->getTracks());
  
        vehicleCouting->process();
  
      }
  
  
  
      key = cvWaitKey(1);
  
    }
  
  
  
    delete vehicleCouting;
  
    delete blobTracking;
  
    delete bgs;
  
  
  
    cvDestroyAllWindows();
  
    cvReleaseCapture(&amp;capture);
  
  
  
    return 0;
  
  }
  
  </iostream>

  Error :

  

• Live stream is gets delayed while processing frame in opencv + python

  18 mars 2021, par Himanshu sharma

  I capture and process an IP camera RTSP stream in a OpenCV 4.4.0.46 on Ubuntu.
Unfortunately the processing takes quite a lot of time, roughly 0.2s per frame, and the stream quickly gets delayed.
Video file have to save for 5 min but by this delaying video file is saved for 3-4 min only.

  


  Can we process faster to overcome delays ?

  


  I have two IP camera which have two diffrent fps_rate(Camera 1 have 18000 and camera 2 have 20 fps)

  


  I am implementing this code in difference Ubuntu PCs

  


  

  • Python 3.8.5 (default, Jul 28 2020, 12:59:40) [GCC 9.3.0] on linux

  


  • Django==3.1.2

  


  • Ubuntu = 18.04 and 20.04

  


  • opencv-contrib-python==4.4.0.46

  


  • opencv-python==4.4.0.46

  


  


  input_stream = 'rtsp://'+username+':'+password+'@'+ip+'/user='+username+'_password='+password+'_channel=0channel_number_stream=0.sdp'
input_stream---> rtsp://admin:Admin123@192.168.1.208/user=admin_password=Admin123_channel=0channel_number_stream=0.sdp

input_stream---> rtsp://Admin:@192.168.1.209/user=Admin_password=_channel=0channel_number_stream=0.sdp

vs = cv2.VideoCapture(input_stream)
fps_rate = int(vs.get(cv2.CAP_PROP_FPS))
I have two IP camera which have two diffrent fps_rate(Camera 1 have 18000 and camera 2 have 20 fps)

video_file_name = 0
start_time = time.time()
while(True):
    ret, frame = vs.read()
    time.sleep(0.2)     # <= Simulate processing time (mask detection, face detection and many detection is hapning)


    ###  Start of  writing a video to disk          
    minute = 5  ## saving a file for 5 minute only then saving another file for 5 min
    second  = 60
    minite_to_save_video = int(minute) * int(second)


    # if we are supposed to be writing a video to disk, initialize
    if time.time() - start_time >= minite_to_save_video or  video_file_name == 0 :
        ## where H = heigth, W = width, C = channel 
        H, W, C = frame.shape
        
        print('time.time()-->',time.time(),'video_file_name-->', video_file_name,  ' #####')
        start_time = time.time()

        video_file_name = str(time.mktime(datetime.datetime.now().timetuple())).replace('.0', '')
        output_save_directory = output_stream+str(int(video_file_name))+'.mp4'


        fourcc = cv2.VideoWriter_fourcc(*'avc1')
        
        writer = cv2.VideoWriter(output_save_directory, fourcc,20.0,(W, H), True)

    # check to see if we should write the frame to disk
    if writer is not None:
        
        try:
            writer.write(frame)

        except Exception as e:
            print('Error in writing video output---> ', e)


  


• How to save media files to Heroku local storage with Django ?

  25 juillet 2022, par Diyan Kalaydzhiev

  Im having a Django REST app with React for client. Im recording a file with React and sending in to Django. When i save it i modify it with ffmpeg and save it again in the same folder with a new name, the ffmpeg command looks like this :

  


  os.system(f"ffmpeg -i {audio_path} -ac 1 -ar 16000 {target_path}")

  


  Because i need a path for my audio both for opening and saving, i can't use cloud stores like "Bucket S3, Cloudinary etc.". And the fact that im using it only for a few seconds and then deleting it makes Heroku (the app is deployed there) the perfect place to save it non-persistent. The problem is that the file isn't getting saved in my library with media files. It saves in the postgre db but doesn't in my filesystem and when i try to access it my program returns that there isn't a file with that name. My question is How can i save media files in Heroku file system and how to access them ?

  


  settings.py

  


  MEDIA_ROOT = os.path.join(BASE_DIR,'EmotionTalk/AI_emotion_recognizer/recordings')
MEDIA_URL = '/'


  


  urls.py

  


  urlpatterns = [
path('admin/', admin.site.urls),
path('', include('EmotionTalk.emotion_talk_app.urls')),
path('auth/', include('EmotionTalk.auth_app.urls')),
path('api-token-auth/', views.obtain_auth_token),
] + static(settings.STATIC_URL, document_root=settings.STATIC_ROOT) \
+ static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)


  


  views.py

  


      def post(self, request):
    file_serializer = RecordingSerializer(data=request.data)

    if file_serializer.is_valid():
        file_serializer.save()

        file_name = file_serializer.data.get('recording')
        owner_id = file_serializer.data.get('owner_id')

        current_emotions_count = len(Profile.objects.get(user_id=owner_id).last_emotions)

        print(file_name)
        recognize_emotion.delay(file_name, owner_id)

        return Response({
            'data': file_serializer.data,
            'current_emotions_count': current_emotions_count
        }, status=status.HTTP_201_CREATED)

    return Response(file_serializer.errors, status=status.HTTP_400_BAD_REQUEST)


  


  tasks.py

  


  def parse_arguments(filename):
import argparse
parser = argparse.ArgumentParser()

new_filename = filename.lstrip('v')

parser.add_argument("audio_path")
parser.add_argument("target_path")

args = parser.parse_args([f'EmotionTalk/AI_emotion_recognizer/recordings/{filename}',
                          f'EmotionTalk/AI_emotion_recognizer/recordings/{new_filename}'])
audio_path = args.audio_path
target_path = args.target_path

if os.path.isfile(audio_path) and audio_path.endswith(".wav"):
    if not target_path.endswith(".wav"):
        target_path += ".wav"
    convert_audio(audio_path, target_path)
    return target_path
else:
    raise TypeError("The audio_path file you specified isn't appropriate for this operation")


  


  parse_arguments is called from recognize_emotion