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• Android-How to pass back frames from FFmpeg back to Android

  23 octobre 2013, par yarin

  It is an architecture question-i am really interesting about the answer

  I building an app with following goals :

  1.record video with effect in real time(using FFmpeg)

  2.display the customized video in real time for the user while he recording

  So,after 1 month of working...i decide to remember that goal number 2 is worth to thinking about :)
  I have a ready skeleton app that record video with effect in real time.
  but i have to preview this customized frame back to the user.

  My options (and this is my question) :

  1.Each frame that pass from onPreviewFrame(byte[] video_frame_data, Camera camera) to ffmpeg with JNI to encode-will sending back to android through the same JNI after i apply the effects(i mean : onPreviewFrame->JNI to FFMPEG->immediately apply effect->send the costumed frame back to android side for display->encode the costumed frame).

  Advantages : it is look like is the most easy to use.

  Disadvantages : use the JNI twice or the passing back the frame could consume time(i really don't now if it really big price to pay,cuz it is only byte array or int array per frame to send to android side)

  2.I heard about openGL on ndk,but i think that the surface it self created on the android side-so is it really going to be better ?
  i prefer to use other surface that i using now in java

  3.Create an video player on FFmpeg to preview each customized frame in real time.

  Thank for your helping,i hope that the first solution is available and not consume to much expensive time in terms of real time processing

• ffmpeg-python video conversion error : malloc of size 36254012 failed on Raspberry Pi

  23 novembre 2021, par Bob Smith

  I am trying to convert a .mkv file into .mp4 format using the ffmpeg-python python library. I have been able to run my script on a Windows machine repeatedly without any issues, however when I run the same script on a Raspberry Pi 4 B I am faced with the same error again and again. Similar to this post, I am faced with the following message :

  


  x264 [error]: malloc of size 36254012 failed
Video encoding failed


  


  I have tried setting max_muxing_queue_size to 9999 as heard this might fix the issue, it had no effect. I tried increasing the gpu RAM from the default 128 MB to as much as 512 MB (I have the 8 GB RAM model so I was not concerned about overall system memory), needless to say this had no effect either.

  


  Finally, I read on a forumn post from someone else with the same error that decresing the number of threads ffmpeg uses to 1 might also solve this issue. This did in fact solve my problem, unfortunately it decreases the speed of the process to a crawl of what it would otherwise be. I was hoping someone might have another idea of how to fix this that would still allow for multiple threads to be used by ffmpeg, or at least have some idea as to what might be causing this issue.

  


  Also it's not particularly useful, but for reference the line that is causing the exception in the code is the following :

  


  ffmpeg.input(video_file).output(out_name, **{'max_muxing_queue_size': '9999'}).run()


  


• Recommendations for real-time pixel-level analysis of television (TV) video

  6 décembre 2011, par Randall Cook

  [Note : This is a rewrite of an earlier question that was considered inappropriate and closed.]

  I need to do some pixel-level analysis of television (TV) video. The exact nature of this analysis is not pertinent, but it basically involves looking at every pixel of every frame of TV video, starting from an MPEG-2 transport stream. The host platform will be server-class, multiprocessor 64-bit Linux machines.

  I need a library that can handle the decoding of the transport stream and present me with the image data in real-time. OpenCV and ffmpeg are two libraries that I am considering for this work. OpenCV is appealing because I have heard it has easy to use APIs and rich image analysis support, but I have no experience using it. I have used ffmpeg in the past for extracting video frame data from files for analysis, but it lacks image analysis support (though Intel's IPP can supplement).

  In addition to general recommendations for approaches to this problem (excluding the actual image analysis), I have some more specific questions that would help me get started :

  1. Are ffmpeg or OpenCV commonly used in industry as a foundation for real-time
     video analysis, or is there something else I should be looking at ?
  2. Can OpenCV decode video frames in real time, and still leave enough
     CPU left over to do nontrivial image analysis, also in real-time ?
  3. Is sufficient to use ffpmeg for MPEG-2 transport stream decoding, or
     is it preferable to just use an MPEG-2 decoding library directly (and if so, which one) ?
  4. Are there particular pixel formats for the output frames that ffmpeg
     or OpenCV is particularly efficient at producing (like RGB, YUV, or YUV422, etc) ?