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• FFMPEG FFBROBE Get Frame Count On Powershell [duplicate]

  27 avril 2020, par ilham zacky

  I am new to FFmpeg, I have some audio and video files, I need to get the duration with frames, I need it in this format H:M:S:F - "00:00:00:00", I am using Powershell

  



  currently, my duration works, but instead of frames, it prints a decimal value.
note : in my output maximum number of frames should be 30

  



  This is my code

  



  $audioId = "$id.m4a"
$videoId = "$id.mp4"

$duration1 = if ((ffprobe -i $audioId 2>&1 | Out-String) -match 'Duration:\s+([\d:"."]+)') { $matches[1] };

$duration = if ((ffmpeg -i $videoId 2>&1 | Out-String) -match 'Duration:\s+([\d:"."]+)') { $matches[1] };

$newduration1 = ("$duration1").Replace(".",":")
$newduration = ("$duration").Replace(".",":")

echo $duration1 
echo $duration



  



  my output be like

  



  00:00:03.48
00:00:03.46



  


• Setting/Installing up OpenCV 2.4.6.1+ on Ubuntu 12.04.02

  30 mai 2016, par Damilola

  I had previously used OpenCV 2.4.5 with some certain configs and packages on Ubuntu 12.04.1 but had issues upgrading to OpenCV 2.4.6.1 on Ubuntu 12.04.2

  I would like to share some ideas (a compilation of noteworthy information gathered from several sources including SO, ubuntu.org, asklinux.org and many other ; and of course by trying several procedures)

  Below is what eventually got me through.

  NOTE : ensure you uninstall any previous installation of OpenCV, FFMpeg and other dependencies previously installed.

  STEP 1 (install ffmpeg and dependencies)

  ---

  # goto http://sourceforge.net/projects/opencvlibrary/files/opencv-unix/
  
  # download the latest stable opencv such as 2.4.6.1 (http://sourceforge.net/projects/opencvlibrary/files/opencv-unix/2.4.5/opencv-2.4.5.1.tar.gz/download) to current directory (such as home or ~/Document)
  
  # cd /opt
  
  # tar -xvf /OpenCV-2.4.6.1.tar.gz
  
  # cd OpenCV-2.4.6.1
  
  # create a foler under current dir (following previous step, this should be ), called prepare
  
  # cd prepare
  
  # Copy the following script to gedit and save as install.sh to current dir, this should be /prepare
  
  # Check corresponding url used in the script for latest versions of the package and replace as required
  
  # Open terminal and navigate to location used above
  
  # sudo chmod +x install.sh
  
  # ./install

  ---

  echo "Removing any pre-installed ffmpeg, x264, and other dependencies (not all the previously installed dependecies)"
  
  sudo apt-get remove ffmpeg x264 libx264-dev libvpx-dev librtmp0 librtmp-dev libopencv-dev
  
  sudo apt-get update
  
  
  
  arch=$(uname -m)
  
  if [ "$arch" == "i686" -o "$arch" == "i386" -o "$arch" == "i486" -o "$arch" == "i586" ]; then
  
  flag=0
  
  else
  
  flag=1
  
  fi
  
  
  
  echo "Installing Dependenices"
  
  sudo apt-get install autoconf automake make g++ curl cmake bzip2 python unzip \
  
    build-essential checkinstall git git-core libass-dev libgpac-dev \
  
    libsdl1.2-dev libtheora-dev libtool libva-dev libvdpau-dev libvorbis-dev libx11-dev \
  
    libxext-dev libxfixes-dev pkg-config texi2html zlib1g-dev
  
  
  
  echo "downloading yasm (assembler used by x264 and FFmpeg)"
  
  # use git or tarball (not both)
  
  wget http://www.tortall.net/projects/yasm/releases/yasm-1.2.0.tar.gz
  
  tar xzvf yasm-1.2.0.tar.gz
  
  cd yasm-1.2.0
  
  
  
  echo "installing yasm"
  
  ./configure
  
  make
  
  sudo make install
  
  cd ..
  
  
  
  echo 'READ NOTE BELOW which was extracted from http://wiki.serviio.org/doku.php?id=build_ffmpeg_linux'
  
  echo 'New version of x264 contains by default support of OpenCL. If not installed or without sense (example Ubuntu 12.04LTS on VMWare) add to configure additional option --disable-opencl. Without this option ffmpeg could not be configured (ERROR: libx264 not found).'
  
  
  
  echo "downloading x264 (H.264 video encoder)"
  
  # use git or tarball (not both)
  
  # git clone http://repo.or.cz/r/x264.git or
  
  git clone git://git.videolan.org/x264.git
  
  cd x264
  
  # wget ftp://ftp.videolan.org/pub/videolan/x264/snapshots/x264-snapshot-20130801-2245-stable.tar.bz2
  
  # tar -xvjf x264-snapshot-20130801-2245-stable.tar.bz2
  
  # cd x264-snapshot-20130801-2245-stable/
  
  
  
  echo "Installing x264"
  
  if [ $flag -eq 0 ]; then
  
  ./configure --enable-static --disable-opencl
  
  else
  
  ./configure --enable-shared --enable-pic --disable-opencl
  
  fi
  
  make
  
  sudo make install
  
  cd ..
  
  
  
  echo "downloading fdk-aac (AAC audio encoder)"
  
  # use git or tarball (not both)
  
  git clone --depth 1 git://github.com/mstorsjo/fdk-aac.git
  
  cd fdk-aac
  
  
  
  echo "installing fdk-aac"
  
  autoreconf -fiv
  
  ./configure --disable-shared
  
  make
  
  sudo make install
  
  cd ..
  
  
  
  echo "installing libmp3lame-dev (MP3 audio encoder.)"
  
  sudo apt-get install libmp3lame-dev
  
  
  
  echo "downloading libopus (Opus audio decoder and encoder.)"
  
  wget http://downloads.xiph.org/releases/opus/opus-1.0.3.tar.gz
  
  tar xzvf opus-1.0.3.tar.gz
  
  cd opus-1.0.3
  
  
  
  echo "installing libopus"
  
  ./configure --disable-shared
  
  make
  
  sudo make install
  
  cd ..
  
  
  
  echo "downloading libvpx VP8/VP9 video encoder and decoder)"
  
  # use git or tarball (not both)
  
  git clone --depth 1 http://git.chromium.org/webm/libvpx.git
  
  cd libvpx
  
  # wget http://webm.googlecode.com/files/libvpx-v1.1.0.tar.bz2 (this seems not to be update, but can still be used if the fedoraproject link below is not available))
  
  # wget http://pkgs.fedoraproject.org/repo/pkgs/libvpx/libvpx-v1.2.0.tar.bz2/400d7c940c5f9d394893d42ae5f463e6/libvpx-v1.2.0.tar.bz2
  
  # tar xvjf libvpx-v1.2.0.tar.bz2
  
  # cd libvpx-v1.2.0
  
  
  
  echo "installing libvpx"
  
  ./configure --disable-examples
  
  make
  
  sudo make install
  
  cd ..
  
  
  
  sudo ldconfig
  
  
  
  echo "downloading ffmpeg"
  
  # git clone http://repo.or.cz/r/ffmpeg.git
  
  git clone git://source.ffmpeg.org/ffmpeg.git
  
  cd ffmpeg/
  
  # wget http://ffmpeg.org/releases/ffmpeg-2.0.tar.bz2
  
  # tar -xvjf ffmpeg-2.0.tar.bz2
  
  # cd ffmpeg-2.0/
  
  
  
  echo "installing ffmpeg" 
  
  if [ $flag -eq 0 ]; then
  
  ./configure --enable-gpl --enable-libass --enable-libfdk-aac --enable-libopus --enable-libfaac --enable-libmp3lame --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libtheora --enable-libvorbis --enable-libx264 --enable-libxvid --enable-nonfree --enable-postproc --enable-version3 --enable-x11grab --enable-libvpx
  
  else
  
  ./configure --enable-gpl --enable-libass --enable-libfdk-aac --enable-libopus --enable-libfaac --enable-libmp3lame --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libtheora --enable-libvorbis --enable-libx264 --enable-libxvid --enable-nonfree --enable-postproc --enable-version3 --enable-x11grab --enable-libvpx --enable-shared
  
  fi
  
  
  
  make
  
  sudo make install
  
  hash -r
  
  
  
  cd .. # move up one level to prepare folder
  
  cd .. # move up one level to opencv folder
  
  
  
  echo "Checking to see if you're using your new ffmpeg"
  
  ffmpeg 2>&1 | head -n1
  
  
  
  sudo ldconfig

  STEP 2 (Install OpenCV and necessary packages)

  echo "Installing Dependenices"    
  
  sudo apt-get install libtiff4-dev libjpeg-dev libjasper-dev
  
  
  
  echo "installing Video I/O libraries, support for Firewire video cameras and video streaming libraries"
  
  sudo apt-get install libav-tools libavcodec-dev libavformat-dev libswscale-dev libdc1394-22-dev libxine-dev libgstreamer0.10-dev libgstreamer-plugins-base0.10-dev libv4l-dev v4l-utils v4l-conf
  
  
  
  echo "installing the Python development environment and the Python Numerical library"
  
  sudo apt-get install python-dev python-numpy
  
  
  
  echo "installing the parallel code processing library (the Intel tbb library)"
  
  sudo apt-get install libtbb-dev
  
  
  
  echo "installing the Qt dev library"
  
  sudo apt-get install libqt4-dev libgtk2.0-dev
  
  
  
  echo "installing other dependencies (if need be it would upgrade current version of the packages)"
  
  sudo apt-get install patch subversion ruby librtmp0 librtmp-dev libfaac-dev libmp3lame-dev libopencore-amrnb-dev libopencore-amrwb-dev libvpx-dev libxvidcore-dev
  
  
  
  echo installing optional packages"
  
  sudo apt-get install libdc1394-utils libdc1394-22-dev libdc1394-22 libjpeg-dev libpng-dev libtiff-dev libjasper-dev

  STEP 3 (run ldconfig)

  # Open a new terminal window
  
  # Open /etc/ld.so.conf and check, 
  
  # if the paths "/usr/lib" and "/usr/local/lib" including the quote exist in the file. If not, add them manually or by
  
      sudo echo "/usr/local/lib" >> /etc/ld.so.conf
  
      sudo echo "/usr/lib" >> /etc/ld.so.conf
  
  # execute the following
  
      sudo ldconfig

  STEP 4a (Build & Install for OS Usage)

  # still ensure you haven't close the new terminal window open in STEP 3
  
  # execute the following
  
  mkdir os_build
  
  cd os_build
  
  cmake -DCMAKE_BUILD_TYPE=RELEASE -DCMAKE_INSTALL_PREFIX=/usr/local -DBUILD_NEW_PYTHON_SUPPORT=ON -DINSTALL_PYTHON_EXAMPLES=ON -DWITH_TBB=ON -DWITH_V4L=ON -DINSTALL_C_EXAMPLES=ON -DBUILD_EXAMPLES=ON -DWITH_QT=ON -DWITH_OPENGL=ON -DWITH_OPENCL=ON -DWITH_EIGEN=ON -DWITH_OPENEXR=ON ..
  
  
  
      make
  
      sudo make install
  
  
  
  # add the following to user environment variable ~/.bashrc
  
      export LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/lib
  
      export PKG_CONFIG_PATH=${PKG_CONFIG_PATH}:/usr/local/lib/pkgconfig
  
  # execute the following
  
      sudo ldconfig
  
  # start to use and enjoy opencv, it should have been install into any of these locations
  
  #   /usr/local/include/opencv2, /usr/local/include/opencv, /usr/include/opencv, /usr/include/opencv2, /usr/local/share/opencv
  
  #   /usr/local/share/OpenCV, /usr/share/opencv, /usr/share/OpenCV, /usr/local/bin/opencv*, /usr/local/lib/libopencv*

  STEP 4b (Build for Java Usage) : OPTIONAL

  # still ensure you haven't close the new terminal window open in STEP 4
  
  # execute the following
  
      cd ..
  
      mkdir java_build
  
      cd java_build
  
      cmake -DCMAKE_BUILD_TYPE=RELEASE -DBUILD_SHARED_LIBS=OFF -DINSTALL_PYTHON_EXAMPLES=ON -DWITH_TBB=ON -DWITH_V4L=ON -DINSTALL_C_EXAMPLES=ON -DBUILD_EXAMPLES=ON -DWITH_QT=ON -DWITH_OPENGL=ON -DWITH_OPENCL=ON -DWITH_EIGEN=ON -DWITH_OPENEXR=ON ..
  
  
  
      make
  
  
  
  # You can check the "java_build/bin" directory to locate the jar and libopencv_java.so file for your development
  
  # As stated in the docs, the Java bindings dynamic library is all-sufficient, i.e. doesn’t depend on other OpenCV libs, but includes all the OpenCV code inside

  STEP 5 (install v4l : Note : installing v4l-utils after opencv installation works for Ubuntu 12.04.2 & OpenCV 2.4.6.1)

  # still ensure you haven't close the new terminal window open in STEP 3
  
  # goto http://www.linuxtv.org/downloads/v4l-utils
  
  # download the latest v4l such as v4l-utils-0.9.5.tar.bz2
  
  # copy the downloaded file to the current terminal dir (following previous step, this should be /prepare)
  
  # execute the following
  
      tar -xvjf v4l-utils-0.9.5.tar.bz2
  
      cd v4l-utils-0.9.5/
  
      ./configure
  
      make
  
      sudo make install
  
      cd ..
  
      cd .. # (to go to )
  
      sudo ldconfig

  Worth Noting

  # To check the path where opencv & other lib files are stored, do:
  
  
  
  
  
  pkg-config --cflags opencv
  
  
  
      (output will come as)
  
      -I/usr/include/opencv
  
  
  
  
  
  
  
  pkg-config --libs opencv
  
  
  
      (output will come as)
  
      -lopencv_core -lopencv_imgproc -lopencv_highgui -lopencv_ --ml -lopencv_video -lopencv_features2d -lopencv_calib3d -lopencv_objdetect -lopencv_contrib -lopencv_legacy -lopencv_flann
  
  
  
  # The above paths are needed to compile your opencv programs, as given in the next illustration.
  
  
  
  # write a simple C program to test, by saving below program in a file named DisplayImage.c
  
  
  
  #include 
  
      #include <opencv2></opencv2>highgui/highgui.hpp>
  
  
  
      int main(int argc, char *argv[]) {
  
          IplImage* img=0; /* pointer to an image */
  
          printf("Hello\n");
  
  
  
          if(argv[1] != 0)
  
              img = cvLoadImage(argv[1], 0); // 1 for color
  
          else
  
              printf("Enter filename\n");
  
  
  
          if(img != 0) {
  
              cvNamedWindow("Display", CV_WINDOW_AUTOSIZE); // create a window
  
              cvShowImage("Display", img); // show image in window
  
              cvWaitKey(0); // wait until user hits a key
  
              cvDestroyWindow("Display");
  
          }
  
          else
  
              printf("File not found\n");
  
  
  
          return 0;
  
      }
  
  
  
  # write a simple C++ program to test, by saving below program in a file named DisplayImage.cpp
  
  
  
  #include 
  
  #include <opencv2></opencv2>opencv.hpp>
  
  #include <opencv2></opencv2>highgui/highgui.hpp>
  
  
  
  using namespace cv;
  
  
  
  int main( int argc, char** argv )
  
  {
  
    Mat image;
  
    image = imread( argv[1], 1 );
  
  
  
    if( argc != 2 || !image.data )
  
      {
  
        printf( "No image data \n" );
  
        return -1;
  
      }
  
  
  
    namedWindow( "Display Image", CV_WINDOW_AUTOSIZE );
  
    imshow( "Display Image", image );
  
  
  
    waitKey(0);
  
  
  
    return 0;
  
  }
  
  
  
  # To compile &amp; run :
  
  
  
  
  
  
  
  g++  `pkg-config --cflags --libs opencv` &amp;&amp; ./a.out img
  
  
  
  or
  
  
  
  
  
  
  
  g++ -I/usr/include/opencv -I/usr/local/include -lopencv_core -lopencv_highgui -lopencv_ml -lopencv_imgproc -lopencv_video -lopencv_features2d -lopencv_calib3d -lopencv_objdetect -lopencv_contrib -lopencv_legacy -lopencv_flann -lopencv_nonfree  &amp;&amp; ./a.out img
  
  
  
  where “img” is the name of any image with extension within the same folder .
  
  You should be able to see “Hello” and the image in a different window.
  
  
  
  If this runs, Congrats! now you can run any C/C++ program with opencv lib.
  
  
  
  
  
  # Now lets simplify the above big command by making a shortcut for it:
  
  go to your local home directory(cd /home/) and open the .bashrc file using gedit(the file will be hidden). Append the following to the file:
  
  
  
  
  
  
  
  alias gcv="g++ -I/usr/include/opencv -I/usr/local/include -lopencv_core -lopencv_highgui -lopencv_ml -lopencv_imgproc -lopencv_video -lopencv_features2d -lopencv_calib3d -lopencv_objdetect -lopencv_contrib -lopencv_legacy -lopencv_flann -lopencv_nonfree"
  
  
  
  and save. Close the terminal and open it again.(as this process requires relogin of the terminal)
  
  
  
  # Now, go to directory containing a sample program &amp; do
  
  
  
  
  
  
  
  gcv  &amp;&amp; ./a.out
  
  
  
  or
  
  
  
  
  
  
  
  gcv 
  
      ./a.out input_img.jpg

  As you can see the commands now become similar to $cc filename.c, $./a.out which are used normally for compiling and executing C/C++ programs.

  ---

  Some ways to check whether all lib files are installed-

  apt-cache search opencv

  returns :

  libcv-dev - Translation package for libcv-dev
  
  libcv2.3 - computer vision library - libcv* translation package
  
  libcvaux-dev - Translation package for libcvaux-dev
  
  libcvaux2.3 - computer vision library - libcvaux translation package
  
  libhighgui-dev - Translation package for libhighgui-dev
  
  libhighgui2.3 - computer vision library - libhighgui translation package
  
  libopencv-calib3d-dev - development files for libopencv-calib3d
  
  libopencv-calib3d2.3 - computer vision Camera Calibration library
  
  libopencv-contrib-dev - development files for libopencv-contrib
  
  libopencv-contrib2.3 - computer vision contrib library
  
  libopencv-core-dev - development files for libopencv-core
  
  libopencv-core2.3 - computer vision core library
  
  libopencv-dev - development files for opencv
  
  libopencv-features2d-dev - development files for libopencv-features2d
  
  libopencv-features2d2.3 - computer vision Feature Detection and Descriptor Extraction library
  
  libopencv-flann-dev - development files for libopencv-flann
  
  libopencv-flann2.3 - computer vision Clustering and Search in Multi-Dimensional spaces library
  
  libopencv-gpu-dev - development files for libopencv-gpu
  
  libopencv-gpu2.3 - computer vision GPU Processing library
  
  libopencv-highgui-dev - development files for libopencv-highgui
  
  libopencv-highgui2.3 - computer vision High-level GUI and Media I/O library
  
  libopencv-imgproc-dev - development files for libopencv-imgproc
  
  libopencv-imgproc2.3 - computer vision Image Processing library
  
  libopencv-legacy-dev - development files for libopencv-legacy
  
  libopencv-legacy2.3 - computer vision legacy library
  
  libopencv-ml-dev - development files for libopencv-ml
  
  libopencv-ml2.3 - computer vision Machine Learning library
  
  libopencv-objdetect-dev - development files for libopencv-objdetect
  
  libopencv-objdetect2.3 - computer vision Object Detection library
  
  libopencv-video-dev - development files for libopencv-video
  
  libopencv-video2.3 - computer vision Video analysis library
  
  opencv-doc - OpenCV documentation and examples
  
  python-opencv - Python bindings for the computer vision library

• Transcoding Modern Formats

  17 août 2014

  I’ve noticed that this blog still gets a decent amount of traffic, particularly to some of the older articles about transcoding. Since I’ve been working on a tool in this space recently, I thought I’d write something up in case it helps folks unravel how to think about transcoding these days.

  The tool I’ve been working on is EditReady, a transcoding app for the Mac. But why do you want to transcode in the first place ?

  Dailies

  After a day of shooting, there are a lot of people who need to see the footage from the day. Most of these folks aren’t equipped with editing suites or viewing stations - they want to view footage on their desktop or mobile device. That can be a problem if you’re shooting ProRes or similar.

  Converting ProRes, DNxHD or MPEG2 footage with EditReady to H.264 is fast and easy. With bulk metadata editing and custom file naming, the management of all the files from the set becomes simpler and more trackable.

  One common workflow would be to drop all the footage from a given shot into EditReady. Use the "set metadata for all" command to attach a consistent reel name to all of the clips. Do some quick spot-checks on the footage using the built in player to make sure it’s what you expect. Use the filename builder to tag all the footage with the reel name and the file creation date. Then, select the H.264 preset and hit convert. Now anyone who needs the footage can easily take the proxies with them on the go, without needing special codecs or players, and regardless of whether they’re working on a PC, a Mac, or even a mobile device.

  If your production is being shot in the Log space, you can use the LUT feature in EditReady to give your viewers a more traditional "video levels" daily. Just load a basic Log to Video Levels LUT for the batch, and your converted files will more closely resemble graded footage.

  Mezzanine Formats

  Even though many modern post production tools can work natively with H.264 from a GoPro or iPhone, there are a variety of downsides to that type of workflow. First and foremost is performance. When you’re working with H.264 in an editor or color correction tool, your computer has to constantly work to decompress the H.264 footage. Those are CPU cycles that aren’t being spent generating effects, responding to user interface clicks, or drawing your previews. Even apps that endeavor to support H.264 natively often get bogged down, or have trouble with all of the "flavors" of H.264 that are in use. For example, mixing and matching H.264 from a GoPro with H.264 from a mobile phone often leads to hiccups or instability.

  By using EditReady to batch transcode all of your footage to a format like ProRes or DNxHD, you get great performance throughout your post production pipeline, and more importantly, you get consistent performance. Since you’ll generally be exporting these formats from other parts of your pipeline as well - getting ProRes effects shots for example - you don’t have to worry about mix-and-match problems cropping up late in the production process either.

  Just like with dailies, the ability to apply bulk or custom metadata to your footage during your initial ingest also makes management easier for the rest of your production. It also makes your final output faster - transcoding from H.264 to another format is generally slower than transcoding from a mezzanine format. Nothing takes the fun out of finishing a project like watching an "exporting" bar endlessly creep along.

  Modernization

  The video industry has gone through a lot of digital formats over the last 20 years. As Mac OS X has been upgraded over the years, it’s gotten harder to play some of those old formats. There’s a lot of irreplaceable footage stored in formats like Sorensen Video, Apple Intermediate Codec, or Apple Animation. It’s important that this footage be moved to a modern format like ProRes or H.264 before it becomes totally unplayable by modern computers. Because EditReady contains a robust, flexible backend with legacy support, you can bring this footage in, select a modern format, and click convert. Back when I started this blog, we were mostly talking about DV and HDV, with a bit of Apple Intermediate Codec mixed in. If you’ve still got footage like that around, it’s time to bring it forward !

  Output

  Finally, the powerful H.264 transcoding pipeline in EditReady means you generate beautiful deliverable H.264 more rapidly than ever. Just drop in your final, edited ProRes, DNxHD, or even uncompressed footage and generate a high quality H.264 for delivery. It’s never been this easy !

  See for yourself

  We released a free trial of EditReady so you can give it a shot yourself. Or drop me a line if you have questions.