Recherche avancée
Autres articles (34)
-
Support audio et vidéo HTML5
10 avril 2011MediaSPIP utilise les balises HTML5 video et audio pour la lecture de documents multimedia en profitant des dernières innovations du W3C supportées par les navigateurs modernes.
Pour les navigateurs plus anciens, le lecteur flash Flowplayer est utilisé.
Le lecteur HTML5 utilisé a été spécifiquement créé pour MediaSPIP : il est complètement modifiable graphiquement pour correspondre à un thème choisi.
Ces technologies permettent de distribuer vidéo et son à la fois sur des ordinateurs conventionnels (...) -
HTML5 audio and video support
13 avril 2011, parMediaSPIP uses HTML5 video and audio tags to play multimedia files, taking advantage of the latest W3C innovations supported by modern browsers.
The MediaSPIP player used has been created specifically for MediaSPIP and can be easily adapted to fit in with a specific theme.
For older browsers the Flowplayer flash fallback is used.
MediaSPIP allows for media playback on major mobile platforms with the above (...) -
De l’upload à la vidéo finale [version standalone]
31 janvier 2010, parLe chemin d’un document audio ou vidéo dans SPIPMotion est divisé en trois étapes distinctes.
Upload et récupération d’informations de la vidéo source
Dans un premier temps, il est nécessaire de créer un article SPIP et de lui joindre le document vidéo "source".
Au moment où ce document est joint à l’article, deux actions supplémentaires au comportement normal sont exécutées : La récupération des informations techniques des flux audio et video du fichier ; La génération d’une vignette : extraction d’une (...)
Sur d’autres sites (3921)
-
OpenCV 4.5.2 takes a long time (>100ms) to retrieve a single frame from a webcam, C++ on Windows 10
9 juin 2021, par Mustard TigerI've been having a tough time getting my webcam working quickly with opencv. Frames take a very long time to read, (a recorded average of 124ms across 500 frames) I've tried on three different computers (running Windows 10) with a logitech C922 webcam. The most recent machine I tested on has a Ryzen 9 3950X, with 32gbs of ram ; no lack of power.


Here is the code :


cv::VideoCapture cap = cv::VideoCapture(m_cameraNum);

// Check if camera opened successfully
if (!cap.isOpened())
{
 m_logger->critical("Error opening video stream or file\n\r");
 return -1;
}

bool result = true;
result &= cap.set(cv::CAP_PROP_FRAME_WIDTH, 1280);
result &= cap.set(cv::CAP_PROP_FRAME_HEIGHT, 720);

bool ready = false;
std::vector<string> timeLog;
timeLog.reserve(50000);
int i = 0;

while (i < 500)
{
 auto start = std::chrono::system_clock::now();
 
 cv::Mat img;
 ready = cap.read(img);

 // If the frame is empty, break immediately
 if (!ready)
 {
 timeLog.push_back("continue");
 continue;
 }

 i++;
 auto end = std::chrono::system_clock::now();
 timeLog.push_back(std::to_string(std::chrono::duration_cast(end - start).count()));
}

for (auto& entry : timeLog)
 m_logger->info(entry);

cap.release();
return 0;
</string>

Notice that I write the elapsed time to a log file at the end of execution. The average time is 124ms for debug and release, and not one instance of "continue" after half a dozen runs.


It doesn't matter if I use USB 2 or USB 3 ports (the camera is USB2) or if I run a debug build or a release build, the log file will show anywhere from 110ms to 130ms of time for each frame. The camera works fine in other app, OBS can get a smooth 1080@30fps or 720@60fps.


Stepping through the debugger and doing a lot of Googling, I've learned the following about my system :


- 

- The backend chosen by default is DSHOW. GStreamer and FFMPEG are also available.
- DSHOW uses FFMPEG somehow (it needs the FFMPEG dll) but I cannot use FFMPEG directly through opencv. Attempting to use cv::VideoCapture(m_cameraNum, cv::CAP_FFMPEG) always fails. It seems like Opencv's interface to FFMPEG is only capable of opening video files.
- Microsoft really screwed up camera devices in Windows a few years back, not sure if this is related to my problem.








Here's a short list of the fixes I have tried, most taken from older SO posts :


- 

- result &= cap.set(cv::CAP_PROP_FRAME_COUNT, 30) ; // Returns false, does nothing
- result &= cap.set(cv::CAP_PROP_CONVERT_RGB, 0) ; // Returns true, does nothing
- result &= cap.set(cv::CAP_PROP_MODE, cv::VideoWriter::fourcc('M', 'J', 'P', 'G')) ; // Returns false, does nothing
- Set registry key from http://alax.info/blog/1693 that should disable the new Windows camera server.
- Updated from 4.5.0 to 4.5.2, no change.
- Asked device manager to find a newer driver, no newer driver found.














I'm out of ideas. Any help ?


-
Should a long Running video processing task to be done client side or server side
27 avril 2021, par Ritwiz SinhaI was creating an application in react for uploading video and using a REST API to send that to the server and store in S3. I also wanted the simple audio version of the video for some other tasks and I am confused as to what might be the better way :


- 

- Creating audio file on the fly when it is needed using node-ffmpeg package and not store it anywhere
- Start converting the video file to audio on the browser client only, and posting that to the server for storage along with the video.
- Just post the video to the server and use queue system for creating a new task for video conversion to audio and then save that to the S3 storage.
The second method seems to be saving some compute power on the server but it might be a problem if the video upload completes, audio conversion is still going on and the client disconnects.
Would appreciate some help, thanks.








-
Python Docker SDK long command to container [duplicate]
2 avril 2021, par Neil BernardI need to send a fairly long command using python docker SDK


ffmpeg -f lavfi -re -i smptebars=duration=60:size=1280x720:rate=30 -f lavfi -re -i sine=frequency=1000:duration=60:sample_rate=44100 -pix_fmt yuv420p -c:v libx264 -b:v 1000k -g 30 -keyint_min 120 -profile:v baseline -preset veryfast -f mpegts "srt://127.0.0.1:4200?pkt_size=1316"


I have an example where you ned to wrap each element in double quotes.


container1 = client.containers.run("alpine", ["echo", "hello", "world"],name='autotest', detach=True)


2 Questions


Is there an elegant way to do this ?
If not how do I handle the bits that already have quotes ?


Syndiquer tout le site
