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• RoQ on Dreamcast

  18 mars 2011, par Multimedia Mike — Sega Dreamcast

  I have been working on that challenge to play back video on the Sega Dreamcast. To review, I asserted that the RoQ format would be a good fit for the Sega Dreamcast hardware. The goal was to play 640x480 video at 30 frames/second. Short version : I have determined that it is possible to decode such video in real time. However, I ran into certain data rate caveats.

  First off : Have you ever wondered if the Dreamcast can read an 80mm optical disc ? It can ! I discovered this when I only had 60 MB of RoQ samples to burn on a disc and a spindle full of these 210MB-capacity 80mm CD-Rs that I never have occasion to use.

  
  
  

  New RoQ Library
  There are open source RoQ decoders out there but I decided to write a new one. A few reasons : 1) RoQ is so simple that I didn’t think it would take too long ; 2) it would be nice to have a RoQ library that is license-compatible (BSD-like) with the rest of the KallistiOS distribution ; 3) the idroq.tar.gz distribution, while license-compatible, has enough issues that I didn’t want to correct it.

  Thankfully, I was correct about the task not being too difficult : I put together a new RoQ decoder in short order. I’m a bit embarrassed to admit that the part I had the most trouble with was properly converting YUV -> RGB.
  
  About the approach I took : While the original idroq.tar.gz decoder maintains YUV 4:2:0 codebooks (which led to chroma bugs during motion compensation) and FFmpeg’s decoder maintains YUV 4:4:4 codebooks, this decoder is built to convert the YUV 4:2:0 vectors into RGB565 vectors during the vector unpacking phase. Thus, the entire frame is rendered in RGB565 — no lengthy YUV -> RGB conversion after decoding — and all pixels are shuffled around as 16-bit units (minor speedup vs. shuffling everything as bytes).

  I also entertained the idea of maintaining YUYV codebooks (since the DC supports that colorspace as a texture format). But I scrapped that idea when I remembered it would lead to the same chroma bleeding problem seen in the original idroq.tar.gz decoder.

  Onto The Dreamcast
  I developed the library on a Linux computer, allowing it to output a series of PNM files for visual verification and debugging. Dropping it into a basic DC/KOS-compatible program was trivial and the first order of business was profiling.

  At first, I profiled the entire decode operation : open file, then read and decode each chunk while tossing away the results. I was roundly disappointed to see that, e.g., an 8.5-second RoQ sample needed a little more than 20 seconds to complete. Not real time. I performed a series of optimizations on the decoding library that netted notable performance gains when profiling on Linux. When I brought these same optimizations over to the DC, decoding time didn’t improve at all. This was my first suspicion that perhaps my assumptions regarding the DC’s optical drive’s data rate were not correct.

  Dreamcast Data Rate Profiling
  Let’s start with some definitions : In terms of data rate, an ’X’, i.e., 1X is the minimum data rate needed to read CD quality audio from a disc. At that speed, a drive should be able to stream 75 sectors each second. When reading mode 1/form 1 CD-ROM data, each sector has 2048 bytes (2 kbytes), so a single-speed data rate should achieve 150 kbytes/sec.

  The Dreamcast is supposed to possess a 12X optical drive. This would imply a maximum data rate of 150 kbytes/sec * 12 = 1800 kbytes/sec.

  Rigging up a trivial experiment using the RoQ samples burned on a few different CD-R discs, the best data rate I can see is about 500-525 kbytes/sec, or around 3.5X.

  Where’s the discrepancy ? My first theory has to do with the fact that not all optical media is created equal. This is why optical drives often advertise a slew of numbers which refer to the best theoretical speed for reading a CD vs. writing a CD-R vs. writing a CD-RW, etc. Perhaps the DC drive can’t read CD-Rs very quickly. To test this theory, I tried streaming a large file from a conventionally mastered CD-ROM. This worked well for the closest CD-ROM I had on hand : I was able to stream data at a rate that works out to about 6.5X.

  I smell a science project for another evening : Profiling read speeds from a mastered CD-ROM, burned CD-R, and also a mastered GD-ROM, on each of the 3 Dreamcast consoles I possess (I’ve heard that there’s variance between optical drives depending on manufacturing run).

  The Good News
  I added a little finer-grained code to profile just the video decoding functions. The good news is that the decoder meets my real time goals : That 8.5-second RoQ sample encoded at 640x480x30fps makes its way through the video decoding functions on the DC in a little less than 5 seconds. If the optical drive can supply the data fast enough, the video decoder can take care of the rest.

  The RoQ encoder included with FFmpeg does not honor any bitrate parameters. Instead, I encoded the same file at 320x240. It reportedly decoded in real time and can be streamed in real time as well.

  I say "reportedly" because I’m simply working from textual output at this point ; the next phase is to hook the decoder up to the display hardware.

• Discord Music bot dosnt play Livestreams anymore

  11 janvier 2019, par Silvinator

  My Discord bot played YT Livestreams all the time, but it stoped working today. The only message i get (in the console) is stream. It plays normal videos, but no streams. the question is, why it stopped working. I did not change any code. Anyone got a idea ?

  client.on("message", async message => {
  
      var args = message.content.substring(prefix.length).split(" ");
  
      if (!message.content.startsWith(prefix)) return;
  
    var searchString = args.slice(1).join(' ');
  
          var url = args[1] ? args[1].replace(/<(.+)>/g, '$1') : '';
  
          var serverQueue = queue.get(message.guild.id);
  
      switch (args[0].toLowerCase()) {
  
        case "play":
  
      var voiceChannel = message.member.voiceChannel;
  
                  if (!voiceChannel) return message.channel.send(`Du willst mit mir Karaoke singen? Da ich eh nichts besseres zu tun habe. Du suchst aber den Voice Channel aus!`);
  
                  var permissions = voiceChannel.permissionsFor(message.client.user);
  
                  if (!permissions.has('CONNECT')) {
  
                          return message.channel.send('I cannot connect to your voice channel, make sure I have the proper permissions!');
  
                  }
  
                  if (!permissions.has('SPEAK')) {
  
                          return message.channel.send('I cannot speak in this voice channel, make sure I have the proper permissions!');
  
                  }
  
        if (url.match(/^https?:\/\/(www.youtube.com|youtube.com)\/playlist(.*)$/)) {
  
                          var playlist = await youtube.getPlaylist(url);
  
                          var videos = await playlist.getVideos();
  
                          for (const video of Object.values(videos)) {
  
                                  var video2 = await youtube.getVideoByID(video.id); // eslint-disable-line no-await-in-loop
  
                                  await handleVideo(video2, message, voiceChannel, true); // eslint-disable-line no-await-in-loop
  
                          }
  
                          return message.channel.send(`Ich habe wohl keine andere wahl... Ich habe **${playlist.title}** der playlist zugefügt`);
  
                  } else {
  
                          try {
  
                                  var video = await youtube.getVideo(url);
  
                          } catch (error) {
  
                                  try {
  
                                          var videos = await youtube.searchVideos(searchString, 10);
  
                                          var index = 0;
  
                                          var videoIndex = 1;
  
                                          var video = await youtube.getVideoByID(videos[videoIndex - 1].id);
  
                                  } catch (err) {
  
                                          console.error(err);
  
                                          return message.channel.send('Gibt es den Song überhaupt?');
  
                                  }
  
                          }
  
                          return handleVideo(video, message, voiceChannel);
  
                  }
  
  break;
  
        case "skip":
  
                  if (!message.member.voiceChannel) return message.channel.send('Du musst schon in den Voice Channel gehen, baka!');
  
                  if (!serverQueue) return message.channel.send('Du musst schon ein song auswählen, baka!');
  
                  serverQueue.connection.dispatcher.end('Skip command has been used!');
  
                  return undefined;
  
          break;
  
        case "stop":
  
                  if (!message.member.voiceChannel) return message.channel.send('Du musst schon in den Voice Channel gehen, baka!');
  
                  if (!serverQueue) return message.channel.send('Du musst schon einen Song auswählen, baka');
  
      serverQueue.connection.dispatcher.end('Stop command has been used!');
  
                  serverQueue.songs = [];
  
                  return undefined;
  
  break;
  
        case "minfo":
  
                  if (!serverQueue) return message.channel.send('Ich spiele immer noch nichts!');
  
                  return message.channel.send(`ퟎ

• Stopping Referrer Spam

  13 mai 2015, par Piwik Core Team — Community

  In this blog post we explain what is Referrer spam, this new kind of spam that has recently appeared on the Internet. We also provide solutions to stop it and preserve the quality of your analytics data.

  What is Referrer Spam ?

  Referrer spam (also known as log spam or referrer bombing) is a kind of spamming aimed at web analytics tools. A spammer bot makes repeated web site requests using a fake referrer URL to the site the spammer wishes to advertise.

  Here is an example of referrer spam in action :

  

  Half of those referrers are spams, here are some well know spammers that you may have seen in your logs : buttons-for-you-website.com, best-seo-offer.com, semalt.com…

  The benefit for spammers is that their website will appear in analytics tools like Piwik or Google Analytics :

  • public analytics reports (or logs) will be indexed by search engines : links to the spammer’s website will improve its ranking
  • curious webmasters are likely to visit their referrers, thus bringing traffic to the spammer’s website

  How to deal with Referrer Spam ?

  Referrer spam is still new and analytics tools are all handling it differently.

  Referrer Spam in Piwik

  At Piwik we started working on mitigating Referrer spam more than a year ago. If you use Piwik and keep it up to date, you do not need to do anything.

  Referrer spammers are automatically excluded from your reports to keep your data clean and useful.

  New spammers are continuously detected and added to Piwik’s blacklist on each update. If you find a new spammer in your analytics data, you can even report it so that it is added to the Piwik’s open referrer blacklist and blocked for everyone.

  Referrer Spam in Google Analytics

  Google Analytics doesn’t offer any spam protection by default. It can however be configured manually using a custom Filter.

  To create a filter in Google Analytics go to the Admin section and click on All Filters. Create a new custom filter that excludes based on the Campaign Source field. In the Filter pattern enter the spammers domains you want to exclude (this is a regular expression) :

  

  If new spammers arise you will need to update this list. You can also use Piwik’s referrer blacklist to exclude all the spammers currently detected.

  Other Analytics Tools

  Many web analytics tools do not yet handle Referrer spam and when using these tools, you will often find a lot of spam data in your Referrer Websites analytics reports.

  If you use an analytics tool that does not exclude Referrer spam, we recommend to contact the vendor and ask them to implement a mechanism to remove these referrer spammers. As of today many analytics vendors still have not mitigated this issue.

  Public List of Referrer Spammers

  At Piwik with the help of our large community we have decided to tackle this growing spam issue. We have created a list of up to date referrer spammers that anyone can edit.

  The list is available in a simple text file on Github : github.com/piwik/referrer-spam-blacklist.

  The list is released under the Public Domain and anyone can use it within their applications to exclude referrer spammers.

  Many people have already contributed new spammers to the list. We invite you to use the list in your apps and websites and help us keep the list up to date !

  Let’s unite and fight the spammers together.

  Happy Analytics !