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• ffmpeg crop detect python using subprocess

  12 mai 2015, par JRM

  I want to use python subprocess to call ffmpeg and use crop detect to find all black in a video. The crop detect return I want to put into a string variable and put in a database. At the moment I can get the process running in terminal and but I am unsure about how to grab the specific part of the terminal (stdout) output :

  the script :

  def cropDetect():
  
      p = subprocess.Popen(["ffmpeg", "-i", "/Desktop/ffprobe_instance/Crop_detect/video_file.mpg", "-vf", "cropdetect=24:16:0", "-vframes", "10", "dummy.mp4"], stdout=subprocess.PIPE)
  
      result = p.communicate()[0]
  
      print result
  
  
  
  
  
  # SCRIPT
  
  cropDetect()

  Result in terminal :
  [Parsed_cropdetect_0 @ 0x7fa1d840cb80] x1:719 x2:0 y1:575 y2:0 w :-704 h :-560 x:714 y:570 pos:432142 pts:44102 t:0.490022 crop=-704 :-560:714:570

  How do I take "crop=-704 :-560:714:570" and put it into a variable that I can store in a database ?

  As per update :

  def cropDetect1():
  
      p = subprocess.check_output(["ffmpeg", "-i", "/Desktop/ffprobe_instance/Crop_detect/video_file.mpg", "-vf", "cropdetect=24:16:0", "-vframes", "10", "dummy.mp4"])
  
      match = re.search("crop\S+", p)
  
      crop_result = None
  
      if match is not None:
  
          crop_result = match.group()
  
          print "hello %s" % crop_result

  I can’t seem to print out the "crop_result" - I am presuming that means that the variable is empty ?

  UPDATE : Found it :

  def detectCropFile(localPath):
  
      fpath = "/xxx/xx/Desktop/Crop_detect/videos/USUV.mp4"
  
      print "File to detect crop: %s " % fpath
  
      p = subprocess.Popen(["ffmpeg", "-i", fpath, "-vf", "cropdetect=24:16:0", "-vframes", "500", "-f", "rawvideo", "-y", "/dev/null"], stdout=subprocess.PIPE, stderr=subprocess.PIPE)
  
      infos = p.stderr.read()
  
      print infos
  
      allCrops = re.findall(CROP_DETECT_LINE + ".*", infos)
  
      print allCrops 
  
      mostCommonCrop = Counter(allCrops).most_common(1)
  
      print "most common crop: %s" % mostCommonCrop
  
      print mostCommonCrop[0][0]
  
      global crop
  
      crop = mostCommonCrop[0][0]
  
      video_rename()

  Use : p = subprocess.Popen(["ffmpeg", "-i", fpath, "-vf", "cropdetect=24:16:0", "-vframes", "500", "-f", "rawvideo", "-y", "/dev/null"], stdout=subprocess.PIPE, stderr=subprocess.PIPE) to pipe it out

• Anomalie #2302 : Problème d’affichage des tableaux longs

  9 mai 2012, par cedric -

  Avec le tableau c’est la règle tableaux-middle : match : "/([^|])(\n[|].*[|]\n)([^|])/UmsS" replace : replace_tableaux is_callback : Y qui renvoie un null et vide tout le texte. Sans doute un problème de mémoire à investiguer.

• ffmpeg trimming audio WAV files and setting timecode

  14 juillet 2022, par user19551045

  I am currently trying to cut an audio file to match the length of a video (without combining the two...just looking at timecodes) and produce a trimmed audio file that has a timecode that will match up with the video, the video is considered the absolute truth.

  


  Currently, the issue is that the timecodes from the original audio file do not get carried over into the new cropped audio file. So, the starting timecode is now 00:00:00:00 instead of say 07:20:02:14. Even using the -timecode commands and trying to hardcode the timecode that way doesn't seem to do the trick. I am wondering if there is any way around this ? I just want to do as minimal to the raw audio as possible...just change the audio file's length while setting the timecodes so the new audio will line up with the video. Any thoughts/suggestions welcome !

  


  Currently I have tried two options that don't seem to work :
using ffmpeg cmds :

  


  
        cmd2 = r'{} -ss "{}" -i "{}" -codec copy -timecode "{}" "{}"'.format(
            FFMPEG_PATH,
            abs(tc_diff_in_seconds),
            audio_path,
            "17074647",
            out_path
        )


  


  and also using pydub :

  


          current_audio = AudioSegment.from_wav("{}".format(audio_path))
        start_time_in_milli = abs(tc_diff_in_seconds*1000)
        end_time_in_milli = start_time_in_milli + video_dur_in_seconds * 1000
        trimmed_audio = current_audio[start_time_in_milli:end_time_in_milli]
        trimmed_audio.export('{}'.format(out_path), format='WAV', parameters=["-timecode", "17:07:46:47"])


  


  Any thoughts/suggestions welcome ! Thanks