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• avcodec/mpeg12dec : Limit maximum A53 CC size

  21 septembre 2020, par Michael Niedermayer

  avcodec/mpeg12dec : Limit maximum A53 CC size
  This is more than 10 times the size of the largest i found. And also alot more
  
  than our encoder could handle (our encoder is limited to max 31)
  
  Without any limit megabyte+ sized blocks can be reallocated millions of times.
  
  Sadly the SCTE-20 spec does not seem to contain any hard limit directly, so this limit here
  
  is arbitrary
  Fixes : Timeout (25sec -> 152ms)
  
  Fixes : 25714/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_MPEG2VIDEO_fuzzer-5713633336885248
  Found-by : continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
  
  Signed-off-by : Michael Niedermayer <michael@niedermayer.cc>
  

  • [DH] libavcodec/mpeg12dec.c

• avformat/hls : improve segment selection when restarting list reception

  30 décembre 2013, par Anssi Hannula

  avformat/hls : improve segment selection when restarting list reception
  Improve selection of the segment sequence number when restarting the
  
  reception of a playlist after it was suspended due to being unneeded
  
  (due to discard flags).
  The current code assumes that each playlist contains matching data with
  
  the same sequence number, while spec 3.4.3 specifically says that that
  
  is not the case. Often subtitle playlists also have longer target
  
  durations as well, causing the selection to be completely wrong.
  Instead prefer using the playlist segment duration information for
  
  non-live playlists, and other means if that is not possible.
  Signed-off-by : Anssi Hannula <anssi.hannula@iki.fi>
  

  • [DH] libavformat/hls.c

• How do I timestamp an excel document using Pandas ?

  16 juillet 2015, par Andy Do

  I have a script that uses FFMPEG and CMD to cut video files based off of an excel document row by row. I would like python to add a timestamp after it is done with a row. Can you guys please help ?

  import subprocess as sp, pandas as pd
  
  
  
  ffmpeg = 'C:/FFMPEG/bin/ffmpeg.exe' # on Windows
  
  datafile = r'C:\Users\A_Do\Dropbox\1. Projects\2. Python\TM Creator\tm_creator_test1.xlsx'
  
  
  
  xl = pd.ExcelFile(datafile,index = False)
  
  df = xl.parse('Sheet1')
  
  
  
  def create_tm():
  
      row_iterator = df.iterrows()
  
       # take first item from row_iterator
  
      for i, row in row_iterator:
  
          infile = row['filename']
  
          outputfile = row['outputfilename']
  
          timein = row['timein']
  
          duration = row['duration']
  
          decision = row['Create TM?']
  
          if decision == "Y":
  
              sp.call(ffmpeg + " -y -i " + infile + " -map 0:0 -map 0:1 -map 0:2 -acodec copy -ss " + str(timein) + " -codec copy -t " + str(duration) + " " + outputfile,shell=True) #this works
  
  
  
          elif decision != decision: #this gets rid of the NaN
  
              break
  
          else:
  
              print "You said you didn't want to make a TM for " + str(infile)
  
  
  
  create_tm()

  Thanks !

  My final code :

  import subprocess as sp, pandas as pd
  
  # (1) new import
  
  from openpyxl import load_workbook
  
  # (2) new import
  
  from datetime import datetime
  
  
  
  ffmpeg = 'D:/FFMPEG/bin/ffmpeg.exe' # on Windows
  
  datafile = r'D:\Dropbox\1. Projects\2. Python\TM Creator\tm_creator_test1.xlsx'
  
  
  
  # (3) open the file in openpyxl first:
  
  book = load_workbook(datafile)
  
  
  
  xl = pd.ExcelFile(datafile,index = False)
  
  df = xl.parse('Sheet1')
  
  
  
  def create_tm():
  
      row_iterator = df.iterrows()
  
       # take first item from row_iterator
  
      for i, row in row_iterator:
  
          infile = row['filename']
  
          outputfile = row['outputfilename']
  
          timein = row['timein']
  
          duration = row['duration']
  
          decision = row['Create TM?']
  
          if decision == "Y":
  
              sp.call(ffmpeg + " -y -i " + infile + " -map 0:0 -map 0:1 -acodec copy -ss " + str(timein) + " -codec copy -t " + str(duration) + " " + outputfile,shell=True) #this works
  
              # (4) Wherever in the code you want to put the timestamp:
  
              df.loc[i, 'Timestamp'] = str(datetime.now())
  
              # (5) This saves the sheet back into the original file, without removing
  
              # any of the old sheets.
  
              writer = pd.ExcelWriter(datafile)
  
              writer.book = book
  
              writer.sheets = dict((ws.title, ws) for ws in book.worksheets)
  
              df.to_excel(writer, index=False)
  
              writer.save()
  
          elif decision != decision: #this gets rid of the NaN
  
              break
  
          else:
  
              print "You said you didn't want to make a TM for " + str(infile)