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• ffpmeg vs ffprobe performance

  13 décembre 2016, par Thomas

  I wanted to try extracting frames at scene changes with ffmpeg, vs. getting the frame numbers with ffprobe and extracting them later.

  But I had a surprise : ffprobe seems to be much slower than ffmpeg, while ffmpeg is taking the frames, resizing and saving them as well.

  ffmpeg command line :

  ffmpeg -hide_banner -y -i d:/test/m/long.mkv -vf "select=gt(scene\,0.4), showinfo, scale=320:-1, tile=12x200" -vsync 0 thumbnails%03d.png

  this takes : 488 seconds

  ffprobe command line :

  ffprobe -show_frames -of compact=p=0 -f lavfi "movie=/test/m/long.mkv,select=gt(scene\,.4)"

  this takes : 899 seconds

  I am missing something ?

• Basic Video Palette Conversion

  20 août 2011, par Multimedia Mike — General, Python

  How do you take a 24-bit RGB image and convert it to an 8-bit paletted image for the purpose of compression using a codec that requires 8-bit input images ? Seems simple enough and that’s what I’m tackling in this post.

  Ask FFmpeg/Libav To Do It
  Ideally, FFmpeg / Libav should be able to handle this automatically. Indeed, FFmpeg used to be able to, at least at the time I wrote this post about ZMBV and was unhappy with FFmpeg’s default results. Somewhere along the line, FFmpeg and Libav lost the ability to do this. I suspect it got removed during some swscale refactoring.

  Still, there’s no telling if the old system would have computed palettes correctly for QuickTime files.

  Distance Approach
  When I started writing my SMC video encoder, I needed to convert RGB (from PNG files) to PAL8 colorspace. The path of least resistance was to match the pixels in the input image to the default 256-color palette that QuickTime assumes (and is hardcoded into FFmpeg/Libav).

  How to perform the matching ? Find the palette entry that is closest to a given input pixel, where "closest" is the minimum distance as computed by the usual distance formula (square root of the sum of the squares of the diffs of all the components).

  
  
  

  That means for each pixel in an image, check the pixel against 256 palette entries (early termination is possible if an acceptable threshold is met). As you might imagine, this can be a bit time-consuming. I wondered about a faster approach...

  Lookup Table
  I think this is the approach that FFmpeg used to use, but I went and derived it for myself after studying the default QuickTime palette table. There’s a pattern there— all of the RGB entries are comprised of combinations of 6 values — 0x00, 0x33, 0x66, 0x99, 0xCC, and 0xFF. If you mix and match these for red, green, and blue values, you come up with 6 * 6 * 6 = 216 different colors. This happens to be identical to the web-safe color palette.

  The first (0th) entry in the table is (FF, FF, FF), followed by (FF, FF, CC), (FF, FF, 99), and on down to (FF, FF, 00) when the green component gets knocked down and step and the next color is (FF, CC, FF). The first 36 palette entries in the table all have a red component of 0xFF. Thus, if an input RGB pixel has a red color closest to 0xFF, it must map to one of those first 36 entries.

  I created a table which maps indices 0..215 to values from 5..0. Each of the R, G, and B components of an input pixel are used to index into this table and derive 3 indices ri, gi, and bi. Finally, the index into the palette table is given by :

    index = ri * 36 + gi * 6 + bi
  

  For example, the pixel (0xFE, 0xFE, 0x01) would yield ri, gi, and bi values of 0, 0, and 5. Therefore :

    index = 0 * 36 + 0 * 6 + 5
  

  The palette index is 5, which maps to color (0xFF, 0xFF, 0x00).

  Validation
  So I was pretty pleased with myself for coming up with that. Now, ideally, swapping out one algorithm for another in my SMC encoder should yield identical results. That wasn’t the case, initially.

  One problem is that the regulation QuickTime palette actually has 40 more entries above and beyond the typical 216-entry color cube (rounding out the grand total of 256 colors). Thus, using the distance approach with the full default table provides for a little more accuracy.

  However, there still seems to be a problem. Let’s check our old standby, the Big Buck Bunny logo image :

  
  
  Distance approach using the full 256-color QuickTime default palette
  
  
  Distance approach using the 216-color palette
  
  
  Table lookup approach using the 216-color palette
  

  I can’t quite account for that big red splotch there. That’s the most notable difference between images 1 and 2 and the only visible difference between images 2 and 3.

  To prove to myself that the distance approach is equivalent to the table approach, I wrote a Python script to iterate through all possible RGB combinations and verify the equivalence. If you’re not up on your base 2 math, that’s 2²⁴ or 16,777,216 colors to run through. I used Python’s multiprocessing module to great effect and really maximized a Core i7 CPU with 8 hardware threads.

  So I’m confident that the palette conversion techniques are sound. The red spot is probably attributable to a bug in my WIP SMC encoder.

  Source Code
  Update August 23, 2011 : Here’s the Python code I used for proving equivalence between the 2 approaches. In terms of leveraging multiple CPUs, it’s possibly the best program I have written to date.

  PLAIN TEXT

  PYTHON :

  1. # !/usr/bin/python
  2.  
  3. from multiprocessing import Pool
  4.  
  5. palette = []
  6. pal8_table = []
  7.  
  8. def process_r(r) :
  9.  counts = []
  10.  
  11.  for i in xrange(216) :
  12.   counts.append(0)
  13.  
  14.  print "r = %d" % (r)
  15.  for g in xrange(256) :
  16.   for b in xrange(256) :
  17.    min_dsqrd = 0xFFFFFFFF
  18.    best_index = 0
  19.    for i in xrange(len(palette)) :
  20.     dr = palette[i][0] - r
  21.     dg = palette[i][1] - g
  22.     db = palette[i][2] - b
  23.     dsqrd = dr * dr + dg * dg + db * db
  24.     if dsqrd <min_dsqrd :
  25.      min_dsqrd = dsqrd
  26.      best_index = i
  27.    counts[best_index] += 1
  28.  
  29.    # check if the distance approach deviates from the table-based approach
  30.    i = best_index
  31.    r = palette[i][0]
  32.    g = palette[i][1]
  33.    b = palette[i][2]
  34.    ri = pal8_table[r]
  35.    gi = pal8_table[g]
  36.    bi = pal8_table[b]
  37.    table_index = ri * 36 + gi * 6 + bi ;
  38.    if table_index != best_index :
  39.     print "(0x%02X 0x%02X 0x%02X) : distance index = %d, table index = %d" % (r, g, b, best_index, table_index)
  40.  
  41.  return counts
  42.  
  43. if __name__ == ’__main__’ :
  44.  counts = []
  45.  for i in xrange(216) :
  46.   counts.append(0)
  47.  
  48.  # initialize reference palette
  49.  color_steps = [ 0xFF, 0xCC, 0x99, 0x66, 0x33, 0x00 ]
  50.  for r in color_steps :
  51.   for g in color_steps :
  52.    for b in color_steps :
  53.     palette.append([r, g, b])
  54.  
  55.  # initialize palette conversion table
  56.  for i in range(0, 26) :
  57.   pal8_table.append(5)
  58.  for i in range(26, 77) :
  59.   pal8_table.append(4)
  60.  for i in range(77, 128) :
  61.   pal8_table.append(3)
  62.  for i in range(128, 179) :
  63.   pal8_table.append(2)
  64.  for i in range(179, 230) :
  65.   pal8_table.append(1)
  66.  for i in range(230, 256) :
  67.   pal8_table.append(0)
  68.  
  69.  # create a pool of worker threads and break up the overall job
  70.  pool = Pool()
  71.  it = pool.imap_unordered(process_r, range(256))
  72.  try :
  73.   while 1 :
  74.    partial_counts = it.next()
  75.    for i in xrange(216) :
  76.     counts[i] += partial_counts[i]
  77.  except StopIteration :
  78.   pass
  79.  
  80.  print "index, count, red, green, blue"
  81.  for i in xrange(len(counts)) :
  82.   print "%d, %d, %d, %d, %d" % (i, counts[i], palette[i][0], palette[i][1], palette[i][2])

• Nexus One

  19 mars 2010, par Mans — Uncategorized

  I have had a Nexus One for about a week (thanks Google), and naturally I have an opinion or two about it.
  

  Hardware

  With the front side dominated by a touch-screen and a lone, round button, the Nexus One appearance is similar to that of most contemporary smartphones. The reverse sports a 5 megapixel camera with LED flash, a Google logo, and a smaller HTC logo. Power button, volume control, and headphone and micro-USB sockets are found along the edges. It is with appreciation I note the lack of a front-facing camera ; the silly idea of video calls is finally put to rest.

  Powering up the phone (I’m beginning to question the applicability of that word), I am immediately enamoured with the display. At 800×480 pixels, the AMOLED display is crystal-clear and easily viewable even in bright light. In a darker environment, the display automatically dims. The display does have one quirk in that the subpixel pattern doesn’t actually have a full RGB triplet for each pixel. The close-up photo below shows the pattern seen when displaying a solid white colour.

  

  The result of this is that fine vertical lines, particularly red or blue ones, look a bit jagged. Most of the time this is not much of a problem, and I find it an acceptable compromise for the higher effective resolution it provides.

  Basic interaction

  The Android system is by now familiar, and the Nexus offers no surprises in basic usage. All the usual applications come pre-installed : browser, email, calendar, contacts, maps, and even voice calls. Many of the applications integrate with a Google account, which is nice. Calendar entries, map placemarks, etc. are automatically shared between desktop and mobile. Gone is the need for the bug-ridden custom synchronisation software with which mobile phones of the past were plagued.

  Launching applications is mostly speedy, and recently used apps are kept loaded as long as memory needs allow. Although this garbage-collection-style of application management, where you are never quite sure whether an app is still running, takes a few moments of acclimatisation, it works reasonably well in day to day use. Most of the applications are well-behaved and save their data before terminating.

  Email

  Two email applications are included out of the box : one generic and one Gmail-only. As I do not use Gmail, I cannot comment on this application. The generic email client supports IMAP, but is rather limited in functionality. Fortunately, a much-enhanced version, K-9, is available for download. The main feature I find lacking here is threaded message view.

  The features, or lack thereof, in the email applications is not, however, of huge importance, as composing email, or any longer piece of text, is something one rather avoids on a system like this. The on-screen keyboard, while falling among the better of its kind, is still slow to use. Lack of tactile feedback means accidentally tapping the wrong key is easily done, and entering numbers or punctuation is an outright chore.

  Browser

  Whatever the Nexus lacks in email abilities, it makes up for with the browser. Surfing the web on a phone has never been this pleasant. Page rendering is quick, and zooming is fast and simple. Even pages not designed for mobile viewing are easy to read with smart reformatting almost entirely eliminating the sideways scrolling which hampered many a mobile browser of old.

  Calls and messaging

  Being a phone, the Nexus One is obviously able to make and receive calls, and it does so with ease. Entering a number or locating a stored contact are both straight-forward operations. During a call, audio is clear and of adequate loudness, although I have yet to use the phone in really noisy surroundings.

  The other traditional task of a mobile phone, messaging, is also well-supported. There isn’t really much to say about this.

  Multimedia

  Having a bit of an interest in most things multimedia, I obviously tested the capabilities of the Nexus by throwing some assorted samples at it, revealing ample space for improvement. With video limited to H.264 and MPEG4, and the only supported audio codecs being AAC, MP3, Vorbis, and AMR, there are many files which will not play.

  To make matters worse, only selected combinations of audio and video will play together. Several video files I tested played without sound, yet when presented with the very same audio data alone, it was correctly decoded. As for container formats, it appears restricted to MP4/MOV, and Ogg (for Vorbis). AVI files are recognised as media files, but I was unable to find an AVI file which would play.

  With a device clearly capable of so much more, the poor multimedia support is nothing short of embarrassing.

  The Market

  Much of the hype surrounding Android revolves around the Market, Google’s virtual marketplace for app authors to sell or give away their creations. The thousands of available applications are broadly categorised, and a search function is available.

  The categorised lists are divided into free and paid sections, while search results, disappointingly, are not. To aid the decision, ratings and comments are displayed alongside the summary and screenshots of each application. Overall, the process of finding and installing an application is mostly painless. While it could certainly be improved, it could also have been much worse.

  The applications themselves are, as hinted above, beyond numerous. Sadly, quality does not quite match up to quantity. The vast majority of the apps are pointless, though occasionally mildly amusing, gimmicks of no practical value. The really good ones, and they do exist, are very hard to find unless one knows precisely what to look for.

  Battery

  Packing great performance into a pocket-size device comes with a price in battery life. The battery in the Nexus lasts considerably shorter time than that in my older, less feature-packed Nokia phone. To some extent this is probably a result of me actually using it a lot more, yet the end result is the same : more frequent recharging. I should probably get used to the idea of recharging the phone every other night.

  Verdict

  The Nexus One is a capable hardware platform running an OS with plenty of potential. The applications are still somewhat lacking (or very hard to find), although the basic features work reasonably well. Hopefully future Android updates will see more and better core applications integrated, and I imagine that over time, I will find third-party apps to solve my problems in a way I like. I am not putting this phone on the shelf just yet.