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• ffmpeg doesnt use all the pictures when creating a video

  9 septembre 2022, par Mikhael Karabas

  I have 75 pictures of the same size for an animation. named 0.png ... 74.png
when running ffmpeg to create a video out of them with 24 fps (commmand and log below) the resulting video instead of expected 75/24 = 3.125 sec. is 2.667 sec in lenght and consists only of first 64 frames(pictures), although ffmpeg tells it has processed 75 frames.
I have checked with

  


  ffmpeg -i output.webm out%%d.png - on the resulting video, it indeed exports 64 first frames and not the rest 11 of them.

  


  Cant undertand what am i doing wrong. please kindly advise.

  


  brief output below.

  


  complete log : https://drive.google.com/file/d/1_J7wLPU9PJZ7jztpiJ8g_bZKPZfiK02L/view?usp=sharing

  


  D:\ffmpeg\ffmpeg-64.exe -report -framerate 24 -f image2 -i %01d.png -c:v libvpx-vp9 -pix_fmt yuva420p -crf 10 -b:v 0 output.webm
ffmpeg started on 2022-09-09 at 19:03:15
Report written to "ffmpeg-20220909-190315.log"
Log level: 48
ffmpeg version 2021-12-17-git-b780b6db64-essentials_build-www.gyan.dev Copyright (c) 2000-2021 the FFmpeg developers
  built with gcc 11.2.0 (Rev2, Built by MSYS2 project)
  configuration: --enable-gpl --enable-version3 --enable-static --disable-w32threads --disable-autodetect --enable-fontconfig --enable-iconv --enable-gnutls --enable-libxml2 --enable-gmp --enable-lzma --enable-zlib --enable-libsrt --enable-libssh --enable-libzmq --enable-avisynth --enable-sdl2 --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxvid --enable-libaom --enable-libopenjpeg --enable-libvpx --enable-libass --enable-libfreetype --enable-libfribidi --enable-libvidstab --enable-libvmaf --enable-libzimg --enable-amf --enable-cuda-llvm --enable-cuvid --enable-ffnvcodec --enable-nvdec --enable-nvenc --enable-d3d11va --enable-dxva2 --enable-libmfx --enable-libgme --enable-libopenmpt --enable-libopencore-amrwb --enable-libmp3lame --enable-libtheora --enable-libvo-amrwbenc --enable-libgsm --enable-libopencore-amrnb --enable-libopus --enable-libspeex --enable-libvorbis --enable-librubberband
  libavutil      57. 11.100 / 57. 11.100
  libavcodec     59. 14.100 / 59. 14.100
  libavformat    59. 10.100 / 59. 10.100
  libavdevice    59.  0.101 / 59.  0.101
  libavfilter     8. 20.100 /  8. 20.100
  libswscale      6.  1.101 /  6.  1.101
  libswresample   4.  0.100 /  4.  0.100
  libpostproc    56.  0.100 / 56.  0.100
Input #0, image2, from '%01d.png':
  Duration: 00:00:03.13, start: 0.000000, bitrate: N/A
  Stream #0:0: Video: png, rgba(pc), 300x400, 24 fps, 24 tbr, 24 tbn
File 'output.webm' already exists. Overwrite? [y/N] y
Stream mapping:
  Stream #0:0 -> #0:0 (png (native) -> vp9 (libvpx-vp9))
Press [q] to stop, [?] for help
[libvpx-vp9 @ 000002dad505c8c0] v1.11.0-62-g7f45e94d9
Output #0, webm, to 'output.webm':
  Metadata:
    encoder         : Lavf59.10.100
  Stream #0:0: Video: vp9, yuva420p(tv, progressive), 300x400, q=2-31, 24 fps, 1k tbn
    Metadata:
      encoder         : Lavc59.14.100 libvpx-vp9
    Side data:
      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A
frame=   75 fps=9.9 q=0.0 Lsize=    1056kB time=00:00:02.58 bitrate=3347.2kbits/s speed=0.342x
video:1036kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 1.942318%


  


• dnn : change dnn interface to replace DNNData* with AVFrame*

  28 août 2020, par Guo, Yejun

  dnn : change dnn interface to replace DNNData* with AVFrame*
  Currently, every filter needs to provide code to transfer data from
  
  AVFrame* to model input (DNNData*), and also from model output
  
  (DNNData*) to AVFrame*. Actually, such transfer can be implemented
  
  within DNN module, and so filter can focus on its own business logic.
  DNN module also exports the function pointer pre_proc and post_proc
  
  in struct DNNModel, just in case that a filter has its special logic
  
  to transfer data between AVFrame* and DNNData*. The default implementation
  
  within DNN module is used if the filter does not set pre/post_proc.
  

  • [DH] configure
  • [DH] libavfilter/dnn/Makefile
  • [DH] libavfilter/dnn/dnn_backend_native.c
  • [DH] libavfilter/dnn/dnn_backend_native.h
  • [DH] libavfilter/dnn/dnn_backend_openvino.c
  • [DH] libavfilter/dnn/dnn_backend_openvino.h
  • [DH] libavfilter/dnn/dnn_backend_tf.c
  • [DH] libavfilter/dnn/dnn_backend_tf.h
  • [DH] libavfilter/dnn/dnn_io_proc.c
  • [DH] libavfilter/dnn/dnn_io_proc.h
  • [DH] libavfilter/dnn_interface.h
  • [DH] libavfilter/vf_derain.c
  • [DH] libavfilter/vf_dnn_processing.c
  • [DH] libavfilter/vf_sr.c

• Bluemix node js build pack to support webm audio conversion

  31 août 2018, par Nimmy Mohandas

  Even after adding ffmpeg to bluemix node js build pack(I tried this https://github.com/BlueChasm/nodejs-buildpack-ffmpeg), it doesn’t support webm audio format conversion.Could anyone please suggest alternate ways to support this issue ?

  Description : I want to do speech to text conversion using Google speech recognition. I am using react native for front-end development. I recorded the voice and generated a webm audio file. Since the google speech recognition doesn’t support webm file format, I converted it into wav format using fluent-ffmpeg. It is working perfectly in my local system, but when I deploy it to the IBM cloud foundry using ffmpeg buildpack(https://github.com/BlueChasm/nodejs-buildpack-ffmpeg), it generates a file without extension. Following are my code,

  router.post('/st', audioUpload.single('audio'), function(req, res, next) {
  
          if (!req.file) {
  
              return res.json({ status: false, error: 'No input given!' });
  
          }
  
  
  
          /**
  
           * convert to .wav
  
           */
  
  
  
  
  
          ffmpeg(req.file.path)
  
              .toFormat('wav')
  
              .inputOptions(['-r 32000',
  
                  '-ac 1'
  
              ])
  
  
  
              .on('error', (err) => {
  
                  console.log('An error occurred: ' + err.message);
  
              })
  
              .save(path.join(__dirname, '..', 'uploads/audio/file.wav'))
  
  
  
          .on('end', () => {
  
  
  
              st.detectAudioFile(path.join(__dirname, '..', 'uploads/audio/file.wav')).then(data => {
  
                      fs.unlink(path.join(__dirname, '..', 'uploads/audio/file.wav'), function(err) {
  
                          if (err) return res.send(err);
  
                          const response = data[0];
  
                          const transcription = response.results
  
                              .map(result => result.alternatives[0].transcript)
  
                              .join('\n');
  
                          return res.json({ transcription });
  
                      }), fs.unlink(req.file.path, function(err) {
  
                          if (err) return res.json(err);
  
                      })
  
  
  
                  })
  
                  .catch(err => {
  
                      res.send({
  
  
  
                          status: false,
  
                          error_code: 400,
  
                          err: err.error || err.message
  
                      });
  
                  });
  
          })
  
      })

  //speech-to-text.js

  const fs = require('fs');
  
  const speech = require('@google-cloud/speech');
  
  
  
  
  
  var detectAudioFile = function(fileName) {
  
  
  
      const Speechclient = new speech.SpeechClient({})
  
  
  
      // Reads a local audio file and converts it to base64
  
      const file = fs.readFileSync(fileName);
  
  
  
      const audioBytes = file.toString('base64');
  
      const audio = {
  
          content: audioBytes,
  
      };
  
      const config = {
  
          // encoding: "FLAC",
  
          // sampleRateHertz: 44100,
  
  
  
          languageCode: 'en-US',
  
      };
  
      const request = {
  
          audio: audio,
  
          config: config,
  
      };
  
      return Speechclient
  
          .recognize(request);
  
  
  
  }
  
  
  
  
  
  
  
  module.exports = {
  
      detectAudioFile
  
  }

  `