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• Piping from ffmpeg to x264 not working

  23 mai 2016, par JiZhaku_San

  I want to encode video file to AVC-I50. I have a vbs script.

  set objShell = WScript.CreateObject ("WScript.Shell")
  
  
  
  objShell.run "cmd.exe /C Processors\ffmpeg.exe -i  """ & PathToInputFile & """ -f lavfi 
  
  -i aevalsrc=0 -loglevel quiet -shortest -filter_complex 
  
  ""[0:1]pan=1|c0=c0[a1],[0:1]pan=1|c0=c1[a2],[0:1]pan=1|c0=c2[a3],[0:1]pan=1|c0=c3[a4]""  
  
  -map ""[a1]"" -c:a pcm_s24le -ar 48000 -y -t """ & duration & """ tmp\01.wav 
  
  -map ""[a2]"" -c:a pcm_s24le -ar 48000 -y -t """ & duration & """ tmp\02.wav 
  
  -map ""[a3]"" -c:a pcm_s24le -ar 48000 -y -t """ & duration & """ tmp\03.wav 
  
  -map ""[a4]"" -c:a pcm_s24le -ar 48000 -y -t """ & duration & """ tmp\04.wav  
  
  -map 0:v -c:v rawvideo -strict -1 -vf format=yuv420p10,fps=fps=30000/1001 
  
  -s 1440x1080 -q:v 0 -an -f yuv4mpegpipe pipe:output.y4m | Processors\x264.exe - 
  
  --demuxer y4m  --frames 1077 --interlaced --tff  --output-csp i420 --no-cabac 
  
  --force-cfr --keyint 1 --colorprim bt709 --transfer bt709 --tune psnr --sar 1:1 
  
  --nal-hrd cbr --pic-struct --videoformat component  --vbv-maxrate 50000 --vbv-bufsize 2000 
  
  --colormatrix bt709 --bitrate 50000 --avcintra-class 50 --output tmp\Result.h264 ", 1, true

  When I try to run in cmd this vbs file, it is working.
  But when I try to run it in C# as Process - it doesn’t.
  Btw. when I try to run it as plain command in cmd it sais that
  "-" is not an input for x264.

• What is White Label Analytics ? Everything You Need to Know

  6 février 2024, par Erin

  Reports are a core part of a marketing agency’s offering. It’s how you build trust with clients by highlighting your efforts and demonstrating your results. 

  But all too often, those reports deliver a jarring and incohesive experience. The culprit ? The logos, colours and names of third-party brands your agency uses to deliver work and create the reports. 

  Luckily, there’s a way to make sure your reports elevate your agency’s stature ; not undermine it. 

  By white labelling your tools, you can deliver a clear and cohesive brand experience — one that strengthens the client relationship rather than diminishing it. 

  In this article, we explain what white label analytics tools are, why it’s important to white label your analytics solution and how you can do it using Matomo. 

  What is white label analytics ?

  White labelling is the process of redesigning a product or service using your company’s brand. The term comes from the act of putting a white label on a product that covers the original branding and allows the reseller to personalise the product.

  White label analytics, then, is a way to customise your analytics software with your agency’s logo and colours. When you white label your analytics, you ensure your reports, dashboards and interface provide a consistent and familiar user experience.

  

  The alternative is to provide your clients with an analytics report containing the logo and branding of your analytics software provider — whether that’s Google Analytics, Matomo, or another tool. 

  For some clients, it can create a confusing experience that takes attention away from your agency’s results.

  Why white label analytics is important

  There are plenty of reasons to white label your analytics tool, from improving your client’s experience to generating additional revenue. Here are four of the most important benefits to know :

  

  Improve the client experience

  You want your clients to have a seamless user experience with your agency’s brand, whether they visit your website, log into their client portal, or read one of your reports. 

  By white labelling your analytics platform, you can give your clients a visually appealing experience that stays in line with the rest of your branding and doesn’t leave them confused about who they are interacting with or which company is providing the service they pay for. 

  This is especially important if your agency uses other third-party tools like a client portal or productivity platform that also allows for custom branding. 

  Strengthen client relationships

  When you use white labelling to remove solution providers’ logos, you ensure your brand gets all of the credit for the hard work you’ve been doing. This can strengthen the agency-client relationship and reaffirm the importance of your agency. 

  But, white labelling allows you to tell a better story through your reports and increases the perceived value you offer. There are no other brands, logos, or names to confuse the narrative or detract from your key points — or to stop the client from understanding just how much value you provide. 

  Save time and increase productivity 

  White labelling your analytics platform can save your team a significant amount of time when creating client reports. 

  There’s no need to carefully screenshot graphs to add them to your own branded report. You can simply email clients a report using your white labelled analytics platform, assuring them of a seamlessly branded experience.

  The upshot is that your team can spend more time on billable work, improving the value they deliver to existing clients or opening up capacity to take on even more work. 

  Increase monetisation opportunities

  Whether you are an agency or consultant, white labelling an analytics solution gives you the opportunity to package and sell analytics as part of your own services. This can open up new revenue streams, help you to diversify your income, and reach a wider audience.

  The beauty of a white label offering is that there is no allusion to the company providing the underlying service.

  The most important elements of an analytics platform to white label 

  A white label analytics solution should offer a broad range of customisation options that range from surface-level branding to functional elements like tracking codes. 

  Below we take a look at the top components you should be able to customise with your chosen platform. 

  Logo and Favicon

  The logo is the first thing clients will see when they open up their analytics platform or look at your reports. It should make your services instantly recognisable, which is why it’s so jarring when clients read a report with another company’s brand slapped on every chart. 

  This should be the very first thing you change since it will be on almost every page and report your client views. Don’t stop there, however. If you send clients web-based reports, you’ll also want to change the platform’s favicon — the small logo you see next to your website in a browser. 

  Customising both your logo and favicon is easy with Matomo. 

  Just head to Administration, then General Settings and click Use a custom Logo under Brand settings.

  

  Upload your brand, click Save, and it will automatically populate your brand in place of the Matomo logo across the platform, just like in the image above.

  Brand name

  Most analytics platforms will mention their brand names repeatedly across the site, so it’s important to change these, too.

  Otherwise, you risk clients reading your analytics reports in detail or playing around with your platform’s settings and getting confused when another seemingly unrelated name keeps popping up. 

  Again, this is easily done with Matomo’s White Label plugin. 

  Head to Administration, then General Settings. Scroll to the bottom of the page to find WhiteLabel settings.

  Enter your brand or product name in the first box and click Save. 

  

  Just like your logo, this will replace every instance of Matomo’s brand name with your own.

  Brand colours

  Changing your analytics platform’s colours to match your own is almost as important as swapping out the logo. 

  Failure to do so could mean the charts and graphs you add to your client reports could cause confusion. 

  You can also use Matomo’s WhiteLabel settings to change the platform’s background and font colours. 

  Just enter a new header background and font colour using hexadecimal values.

  

  This change will also apply to automated email reports. 

  Custom tracking

  Tracking requests and links are an overlooked element of analytics when it comes to white labelling. Most people wouldn’t think twice about them, but they are an easy way for someone in the know to identify which platform you are using. 

  With Matomo’s White Label plugin, it’s possible to customise every request Matomo makes to your clients’ websites. 

  If left unbranded, tracking requests contain the following references : matomo.js and matomo.php. 

  By clicking the Whitelabel tracking endpoint box on the WhiteLabel settings page, those references will be replaced with js/tracker.js and js/tracker.php

  You’ll need to update your tracking code to reflect these changes, otherwise, requests will still contain Matomo branding. 

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  Links

  Finally, you’ll want to remove any links to any additional content offered by the analytics company. These are usually included to improve the user experience, but they are best removed if you are letting clients access your platform. 

  With Matomo, you can remove all links by clicking the relevant box in WhiteLabel settings. 

  You can also use the Show Marketplace only to Super Users checkbox to limit the visibility of Matomo’s Marketplace to everyone bar Super Users.

  Can you white label Google Analytics ?

  In a word : no. 

  Google Analytics might be the most popular analytics platform, but it comes up short if you want to customise its appearance. 

  This can be a particular problem for agencies that need to stand out from competitors offering the same generic reports. You can add more context, detail and graphs to your analytics reports, of course. But you’ll never be able to create completely custom, brand-cohesive reports using Google Analytics. 

  3 analytics platforms you can white label

  While you can’t white label Google Analytics, there are several web analytics providers that do offer a white labelling service. Here are three of the best :

  Matomo

  As you’ve already seen, Matomo is the ideal web analytics platform if you want to let your own brand shine through. Matomo lets you personalise the entire dashboard and all of your reports. That includes :

  • Adding your brand logo and favicon
  • Changing the font and background colours 
  • Removing third-party links
  • Tracking using custom URLs 
  • Develop your own custom theme

  Matomo offers a 21-day free trial (no credit card required). If you want to get remove the Matomo branding, you need the White Label plugin, which starts at just $179 per year after a free trial.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  Clicky

  Clicky is a simple, privacy-focused web analytics platform with a white label offering. Like Matomo, you can add your logo and change the platform’s colours. 

  Clicky offers a seven-day free trial and charges a $99 setup fee, with prices starting from $49 and rising to $399. 

  Plausible 

  Plausible is another privacy-focused Google Analytics alternative that offers white labelling. The difference here is that it’s pretty complex to set up. 

  Rather than customising Plausible’s platform, for instance, you need to embed its dashboard into your own user interface. If you want to create your own custom dashboard, you’ll need to use an API. 

  Plausible offers a 30-day free trial.

  Leverage white label analytics today with Matomo

  Don’t put up with confusing unbranded clients a moment longer. White label your analytics platform so the next time you sit down to share insights with your clients, they’ll only see one brand : yours.

  Matomo makes it quick and easy to customise the look of your analytics platform and all of the reports you generate. If you already use Matomo, try the White Label plugin free for 30 days.

  If not, try Matomo with a free 21-day trial. No credit card required. 

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

  Your email address
  

  Your website address
  

  Your Analytics subdomain will be .matomo.cloud (change)

  Choose your analytics subdomain
  

  .matomo.cloud

  I accept the terms and conditions and data processing agreement (DPA)

  
  Your information will be used to create an account on our cloud service. For more information please consult our privacy policy.
  
  
  

  Start improving your websites now

  

• How to Stream RTP (IP camera) Into React App setup

  10 novembre 2024, par sharon2469

  I am trying to transfer a live broadcast from an IP camera or any other broadcast coming from an RTP/RTSP source to my REACT application. BUT MUST BE LIVE

  


  My setup at the moment is :

  


  IP Camera -> (RTP) -> FFmpeg -> (udp) -> Server(nodeJs) -> (WebRTC) -> React app

  


  In the current situation, There is almost no delay, but there are some things here that I can't avoid and I can't understand why, and here is my question :

  


  1) First, is the SETUP even correct and this is the only way to Stream RTP video in Web app ?

  


  2) Is it possible to avoid re-encode the stream , RTP transmission necessarily comes in H.264, hence I don't really need to execute the following command :

  


      return spawn('ffmpeg', [
    '-re',                              // Read input at its native frame rate Important for live-streaming
    '-probesize', '32',                 // Set probing size to 32 bytes (32 is minimum)
    '-analyzeduration', '1000000',      // An input duration of 1 second
    '-c:v', 'h264',                     // Video codec of input video
    '-i', 'rtp://238.0.0.2:48888',      // Input stream URL
    '-map', '0:v?',                     // Select video from input stream
    '-c:v', 'libx264',                  // Video codec of output stream
    '-preset', 'ultrafast',             // Faster encoding for lower latency
    '-tune', 'zerolatency',             // Optimize for zero latency
    // '-s', '768x480',                    // Adjust the resolution (experiment with values)
    '-f', 'rtp', `rtp://127.0.0.1:${udpPort}` // Output stream URL
]);


  


  As you can se in this command I re-encode to libx264, But if I set FFMPEG a parameter '-c:v' :'copy' instead of '-c:v', 'libx264' then FFMPEG throw an error says : that it doesn't know how to encode h264 and only knows what is libx264-> Basically, I want to stop the re-encode because there is really no need for it, because the stream is already encoded to H264. Are there certain recommendations that can be made ?

  


  3) I thought about giving up the FFMPEG completely, but the RTP packets arrive at a size of 1200+ BYTES when WEBRTC is limited to up to 1280 BYTE. Is there a way to manage these sabotages without damaging the video and is it to enter this world ? I guess there is the whole story with the JITTER BUFFER here

  


  This is my server side code (THIS IS JUST A TEST CODE)

  


  import {
    MediaStreamTrack,
    randomPort,
    RTCPeerConnection,
    RTCRtpCodecParameters,
    RtpPacket,
} from 'werift'
import {Server} from "ws";
import {createSocket} from "dgram";
import {spawn} from "child_process";
import LoggerFactory from "./logger/loggerFactory";

//

const log = LoggerFactory.getLogger('ServerMedia')

// Websocket server -> WebRTC
const serverPort = 8888
const server = new Server({port: serverPort});
log.info(`Server Media start om port: ${serverPort}`);

// UDP server -> ffmpeg
const udpPort = 48888
const udp = createSocket("udp4");
// udp.bind(udpPort, () => {
//     udp.addMembership("238.0.0.2");
// })
udp.bind(udpPort)
log.info(`UDP port: ${udpPort}`)


const createFFmpegProcess = () => {
    log.info(`Start ffmpeg process`)
    return spawn('ffmpeg', [
        '-re',                              // Read input at its native frame rate Important for live-streaming
        '-probesize', '32',                 // Set probing size to 32 bytes (32 is minimum)
        '-analyzeduration', '1000000',      // An input duration of 1 second
        '-c:v', 'h264',                     // Video codec of input video
        '-i', 'rtp://238.0.0.2:48888',      // Input stream URL
        '-map', '0:v?',                     // Select video from input stream
        '-c:v', 'libx264',                  // Video codec of output stream
        '-preset', 'ultrafast',             // Faster encoding for lower latency
        '-tune', 'zerolatency',             // Optimize for zero latency
        // '-s', '768x480',                    // Adjust the resolution (experiment with values)
        '-f', 'rtp', `rtp://127.0.0.1:${udpPort}` // Output stream URL
    ]);

}

let ffmpegProcess = createFFmpegProcess();


const attachFFmpegListeners = () => {
    // Capture standard output and print it
    ffmpegProcess.stdout.on('data', (data) => {
        log.info(`FFMPEG process stdout: ${data}`);
    });

    // Capture standard error and print it
    ffmpegProcess.stderr.on('data', (data) => {
        console.error(`ffmpeg stderr: ${data}`);
    });

    // Listen for the exit event
    ffmpegProcess.on('exit', (code, signal) => {
        if (code !== null) {
            log.info(`ffmpeg process exited with code ${code}`);
        } else if (signal !== null) {
            log.info(`ffmpeg process killed with signal ${signal}`);
        }
    });
};


attachFFmpegListeners();


server.on("connection", async (socket) => {
    const payloadType = 96; // It is a numerical value that is assigned to each codec in the SDP offer/answer exchange -> for H264
    // Create a peer connection with the codec parameters set in advance.
    const pc = new RTCPeerConnection({
        codecs: {
            audio: [],
            video: [
                new RTCRtpCodecParameters({
                    mimeType: "video/H264",
                    clockRate: 90000, // 90000 is the default value for H264
                    payloadType: payloadType,
                }),
            ],
        },
    });

    const track = new MediaStreamTrack({kind: "video"});


    udp.on("message", (data) => {
        console.log(data)
        const rtp = RtpPacket.deSerialize(data);
        rtp.header.payloadType = payloadType;
        track.writeRtp(rtp);
    });

    udp.on("error", (err) => {
        console.log(err)

    });

    udp.on("close", () => {
        console.log("close")
    });

    pc.addTransceiver(track, {direction: "sendonly"});

    await pc.setLocalDescription(await pc.createOffer());
    const sdp = JSON.stringify(pc.localDescription);
    socket.send(sdp);

    socket.on("message", (data: any) => {
        if (data.toString() === 'resetFFMPEG') {
            ffmpegProcess.kill('SIGINT');
            log.info(`FFMPEG process killed`)
            setTimeout(() => {
                ffmpegProcess = createFFmpegProcess();
                attachFFmpegListeners();
            }, 5000)
        } else {
            pc.setRemoteDescription(JSON.parse(data));
        }
    });
});


  


  And this fronted :

  


  &#xA;&#xA;&#xA;    &#xA;    &#xA;    <code class="echappe-js">&lt;script&amp;#xA;            crossorigin&amp;#xA;            src=&quot;https://unpkg.com/react@16/umd/react.development.js&quot;&amp;#xA;    &gt;&lt;/script&gt;&#xA;    &lt;script&amp;#xA;            crossorigin&amp;#xA;            src=&quot;https://unpkg.com/react-dom@16/umd/react-dom.development.js&quot;&amp;#xA;    &gt;&lt;/script&gt;&#xA;    &lt;script&amp;#xA;            crossorigin&amp;#xA;            src=&quot;https://cdnjs.cloudflare.com/ajax/libs/babel-core/5.8.34/browser.min.js&quot;&amp;#xA;    &gt;&lt;/script&gt;&#xA;    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/babel-regenerator-runtime@6.5.0/runtime.min.js&quot;&gt;&lt;/script&gt;&#xA;&#xA;&#xA;
  &#xA;    
  
  &#xA;
  
  &#xA;&lt;script type=&quot;text/babel&quot;&gt;&amp;#xA;    let rtc;&amp;#xA;&amp;#xA;    const App = () =&gt; {&amp;#xA;        const [log, setLog] = React.useState([]);&amp;#xA;        const videoRef = React.useRef();&amp;#xA;        const socket = new WebSocket(&quot;ws://localhost:8888&quot;);&amp;#xA;        const [peer, setPeer] = React.useState(null); // Add state to keep track of the peer connection&amp;#xA;&amp;#xA;        React.useEffect(() =&gt; {&amp;#xA;            (async () =&gt; {&amp;#xA;                await new Promise((r) =&gt; (socket.onopen = r));&amp;#xA;                console.log(&quot;open websocket&quot;);&amp;#xA;&amp;#xA;                const handleOffer = async (offer) =&gt; {&amp;#xA;                    console.log(&quot;new offer&quot;, offer.sdp);&amp;#xA;&amp;#xA;                    const updatedPeer = new RTCPeerConnection({&amp;#xA;                        iceServers: [],&amp;#xA;                        sdpSemantics: &quot;unified-plan&quot;,&amp;#xA;                    });&amp;#xA;&amp;#xA;                    updatedPeer.onicecandidate = ({ candidate }) =&gt; {&amp;#xA;                        if (!candidate) {&amp;#xA;                            const sdp = JSON.stringify(updatedPeer.localDescription);&amp;#xA;                            console.log(sdp);&amp;#xA;                            socket.send(sdp);&amp;#xA;                        }&amp;#xA;                    };&amp;#xA;&amp;#xA;                    updatedPeer.oniceconnectionstatechange = () =&gt; {&amp;#xA;                        console.log(&amp;#xA;                            &quot;oniceconnectionstatechange&quot;,&amp;#xA;                            updatedPeer.iceConnectionState&amp;#xA;                        );&amp;#xA;                    };&amp;#xA;&amp;#xA;                    updatedPeer.ontrack = (e) =&gt; {&amp;#xA;                        console.log(&quot;ontrack&quot;, e);&amp;#xA;                        videoRef.current.srcObject = e.streams[0];&amp;#xA;                    };&amp;#xA;&amp;#xA;                    await updatedPeer.setRemoteDescription(offer);&amp;#xA;                    const answer = await updatedPeer.createAnswer();&amp;#xA;                    await updatedPeer.setLocalDescription(answer);&amp;#xA;&amp;#xA;                    setPeer(updatedPeer);&amp;#xA;                };&amp;#xA;&amp;#xA;                socket.onmessage = (ev) =&gt; {&amp;#xA;                    const data = JSON.parse(ev.data);&amp;#xA;                    if (data.type === &quot;offer&quot;) {&amp;#xA;                        handleOffer(data);&amp;#xA;                    } else if (data.type === &quot;resetFFMPEG&quot;) {&amp;#xA;                        // Handle the resetFFMPEG message&amp;#xA;                        console.log(&quot;FFmpeg reset requested&quot;);&amp;#xA;                    }&amp;#xA;                };&amp;#xA;            })();&amp;#xA;        }, []); // Added socket as a dependency to the useEffect hook&amp;#xA;&amp;#xA;        const sendRequestToResetFFmpeg = () =&gt; {&amp;#xA;            socket.send(&quot;resetFFMPEG&quot;);&amp;#xA;        };&amp;#xA;&amp;#xA;        return (&amp;#xA;            &lt;div&gt;&amp;#xA;                Video: &amp;#xA;                &lt;video ref={videoRef} autoPlay muted /&gt;&amp;#xA;                &lt;button onClick={() =&gt; sendRequestToResetFFmpeg()}&gt;Reset FFMPEG&lt;/button&gt;&amp;#xA;            &lt;/div&gt;&amp;#xA;        );&amp;#xA;    };&amp;#xA;&amp;#xA;    ReactDOM.render(&lt;App /&gt;, document.getElementById(&quot;app1&quot;));&amp;#xA;&lt;/script&gt;&#xA;&#xA;&#xA;