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• swscale/aarch64 : use multiply accumulate and increase vector factor to 4

  17 novembre 2019, par Sebastian Pop

  swscale/aarch64 : use multiply accumulate and increase vector factor to 4
  This patch implements ff_hscale_8_to_15_neon with NEON fused multiply accumulate
  
  and bumps the vectorization factor from 2 to 4.
  
  The speedup is of 25% on Graviton1 A1 instances based on A-72 cpus :
  $ ffmpeg -nostats -f lavfi -i testsrc2=4k:d=2 -vf bench=start,scale=1024x1024,bench=stop -f null -
  
  before : t:0.040303 avg:0.040287 max:0.040371 min:0.039214
  
  after :  t:0.032168 avg:0.032215 max:0.033081 min:0.032146
  The speedup is of 39% on Graviton2 m6g instances based on Neoverse-N1 cpus :
  
  $ ffmpeg -nostats -f lavfi -i testsrc2=4k:d=2 -vf bench=start,scale=1024x1024,bench=stop -f null -
  
  before : t:0.019446 avg:0.019423 max:0.019493 min:0.019181
  
  after :  t:0.014015 avg:0.014096 max:0.015018 min:0.013971
  Tested with `make check` on aarch64-linux.
  Signed-off-by : Sebastian Pop <spop@amazon.com>
  
  Reviewed-by : Jean-Baptiste Kempf <jb@videolan.org>
  
  Signed-off-by : Michael Niedermayer <michael@niedermayer.cc>
  

  • [DH] libswscale/aarch64/hscale.S

• FFmpeg transcode GIF into Mp4 and Mp4 to AVI using GPU

  9 octobre 2023, par Cristian

  I'm trying to convert GIF animated to mp4 and mp4 to AVI with FFmpeg.

  


  I started to use just the CPU, but I have to process millions of GIFs/mp4 content pieces. So, I started to have a lot of errors processing them, and it ended as a bottleneck. Therefore, I'm trying to use GPU to process the videos.

  


  Converting GIF to mp4 with CPU, I run the following command :

  


  ffmpeg -i animated.gif -movflags faststart -pix_fmt yuv420p -vf "scale=trunc(iw/2)*2:trunc(ih/2)*2" video.mp4


  


  Using the GPU I'm trying the following :

  


  ffmpeg
  -y
  -hwaccel nvdec
  -hwaccel_output_format cuda
  -i gifInputPath
  -threads 1
  -filter_threads 1
  -c:v h264_nvenc
  -vf hwupload_cuda,scale_cuda=-2:320:240:format=yuv420p
  -gpu 0
   mp4VideoPath


  


  The above command generates an exit status 1.

  


  The following is the dmesg command log

  


  Converting mp4 videos to AVI videos I'm running the following command

  


  ffmpeg
-i videoInputPath
-vcodec rawvideo
-pix_fmt yuv420p
-acodec pcm_s16le
-ar 44100
-ac 2
-s 320x240
-r 4
-f avi
aviOutputVideoPath


  


  For GPU I tried :

  


  ffmpeg
 -y
 -hwaccel cuda
 -hwaccel_output_format cuda
 -i videoInputPath
 -threads 1
 -filter_threads 1
 -c:a pcm_s16le
 -ac 2
 -ar 44100
 -c:v h264_nvenc
 -vf hwupload_cudascale_cuda=-2:320:240:format=yuv420p
 -r 4
 -f avi
 -gpu 0
 aviOutputVideoPath


  


  The following is the dmseg output is log

  


  


  1. What should be the best command for converting the GIF into Mp4 and Mp4 into AVI based on CPU configuration using the GPU(Amazon Nvidia t4) for best performance, low CPU, and moderated GPU consumption ?

     


  


  2. What are the best suggestions to Process these content pieces concurrently using GPU ?

     


  


  


  Note : I'm using Golang to execute the FFmpeg commands.

  


• A ffmpeg comman canwork in cmd but not in Python using subprocess.call() or os.system()

  6 juin 2018, par Starrysky

  I wanna transfer a .mp3 to .wav. This is my command :
  ffmpeg -i a.mp3 -ar 16000 -ac 1 -acodec pcm_s16le a.wav

  It worked well in cmd

  C:\Users\starrysky\Documents\GitHub\bing_pic\html>ffmpeg -i a.mp3 -ar 16000 -ac 1 -acodec pcm_s16le a.wav
  
  ffmpeg version N-86482-gbc40674 Copyright (c) 2000-2017 the FFmpeg developers
  
    built with gcc 7.1.0 (GCC)
  
    configuration: --enable-gpl --enable-version3 --enable-cuda --enable-cuvid --enable-d3d11va --enable-dxva2 --enable-libmfx --enable-nvenc --enable-avisynth --enable-bzlib --enable-fontconfig --enable-frei0r --enable-gnutls --enable-iconv --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libfreetype --enable-libgme --enable-libgsm --enable-libilbc --enable-libmodplug --enable-libmp3lame --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenh264 --enable-libopenjpeg --enable-libopus --enable-librtmp --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvo-amrwbenc --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxavs --enable-libxvid --enable-libzimg --enable-lzma --enable-zlib
  
    libavutil      55. 66.100 / 55. 66.100
  
    libavcodec     57. 99.100 / 57. 99.100
  
    libavformat    57. 73.100 / 57. 73.100
  
    libavdevice    57.  7.100 / 57.  7.100
  
    libavfilter     6. 92.100 /  6. 92.100
  
    libswscale      4.  7.101 /  4.  7.101
  
    libswresample   2.  8.100 /  2.  8.100
  
    libpostproc    54.  6.100 / 54.  6.100
  
  Input #0, mp3, from 'a.mp3':
  
    Metadata:
  
      encoder         : Lavf54.6.100
  
    Duration: 00:00:01.87, start: 0.000000, bitrate: 8 kb/s
  
      Stream #0:0: Audio: mp3, 8000 Hz, mono, s16p, 8 kb/s
  
  Stream mapping:
  
    Stream #0:0 -> #0:0 (mp3 (native) -> pcm_s16le (native))
  
  Press [q] to stop, [?] for help
  
  Output #0, wav, to 'a.wav':
  
    Metadata:
  
      ISFT            : Lavf57.73.100
  
      Stream #0:0: Audio: pcm_s16le ([1][0][0][0] / 0x0001), 16000 Hz, mono, s16, 256 kb/s
  
      Metadata:
  
        encoder         : Lavc57.99.100 pcm_s16le
  
  size=      59kB time=00:00:01.87 bitrate= 256.3kbits/s speed= 187x
  
  video:0kB audio:58kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.130208%

  but when I moved it into my python program, something strange happened.

  >>> C:\Users\starrysky\Documents\GitHub\bing_pic\html\
  
  'ffmpeg' �����ڲ����ⲿ���Ҳ���ǿ����еij���
  
  ���������ļ���
  
  1 Command 'ffmpeg -i a.mp3 -ar 16000 -ac 1 -acodec pcm_s16le a.wav' returned non-zero exit status 1.
  
  文件错误啊，亲
  
  [WinError 2] 系统找不到指定的文件。: 'a.wav'

  This is part of my python code :

  @bot.register(wife, RECORDING)
  
  def translate_sound(msg):
  
      msg.get_file(save_path='a.mp3')
  
      path = os.path.abspath('.')+'\\'
  
      print(path)
  
      try:
  
          subprocess.check_call('ffmpeg -i a.mp3 -ar 16000 -ac 1 -acodec pcm_s16le a.wav', shell=True)
  
          # ''
  
      except Exception as e:
  
          print(1, e)
  
      wav_to_text('a.wav')
  
      try:
  
          os.remove('a.wav')
  
      except Exception as e:
  
          print(e)

  ---

  # 调用百度语音识别API
  
  def get_token():
  
      URL = 'http://openapi.baidu.com/oauth/2.0/token'
  
      _params = urllib.parse.urlencode({'grant_type': b'client_credentials',
  
                                        'client_id': b''
  
                                        'client_secret': b''})
  
      _res = urllib.request.Request(URL, _params.encode())
  
      _response = urllib.request.urlopen(_res)
  
      _data = _response.read()
  
      _data = json.loads(_data)
  
      return _data['access_token']
  
  
  
  
  
  def wav_to_text(wav_file):
  
      try:
  
          wav_file = open(wav_file, 'rb')
  
      except IOError:
  
          print('文件错误啊，亲')
  
          return
  
      wav_file = wave.open(wav_file)
  
      n_frames = wav_file.getnframes()
  
      print('n_frames ', n_frames)
  
      frame_rate = wav_file.getframerate()
  
      print("frame_rate ", frame_rate)
  
      if n_frames == 1 or frame_rate not in (8000, 16000):
  
          print('不符合格式')
  
          return
  
      audio = wav_file.readframes(n_frames)
  
      seconds = n_frames/frame_rate+1
  
      minute = int(seconds/60 + 1)
  
      for i in range(0, minute):
  
          sub_audio = audio[i*60*frame_rate:(i+1)*60*frame_rate]
  
          base_data = base64.b64encode(sub_audio)
  
          data = {"format": "wav",
  
                  "token": get_token(),
  
                  "len": len(sub_audio),
  
                  "rate": frame_rate,
  
                  "speech": base_data.decode(),
  
                  "cuid": "B8-AC-6F-2D-7A-94",
  
                  "channel": 1}
  
          data = json.dumps(data)
  
          res = urllib.request.Request('http://vop.baidu.com/server_api',
  
                                data.encode(),
  
                                {'content-type': 'application/json'})
  
          response = urllib.request.urlopen(res)
  
          res_data = json.loads(response.read())
  
          try:
  
              print(res_data['result'][0])
  
          except Exception as e:
  
              print(e)

  What happened ?