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• How to Choose the Optimal Multi-Touch Attribution Model for Your Organisation

  13 mars 2023, par Erin — Analytics Tips

  If you struggle to connect the dots on your customer journeys, you are researching the correct solution. 

  Multi-channel attribution models allow you to better understand the users’ paths to conversion and identify key channels and marketing assets that assist them.

  That said, each attribution model has inherent limitations, which make the selection process even harder.

  This guide explains how to choose the optimal multi-touch attribution model. We cover the pros and cons of popular attribution models, main evaluation criteria and how-to instructions for model implementation. 

  Pros and Cons of Different Attribution Models 

  

  First Interaction 

  First Interaction attribution model (also known as first touch) assigns full credit to the conversion to the first channel, which brought in a lead. However, it doesn’t report other interactions the visitor had before converting.

  Marketers, who are primarily focused on demand generation and user acquisition, find the first touch attribution model useful to evaluate and optimise top-of-the-funnel (ToFU). 

  Pros 

  • Reflects the start of the customer journey
  • Shows channels that bring in the best-qualified leads 
  • Helps track brand awareness campaigns

  Cons 

  • Ignores the impact of later interactions at the middle and bottom of the funnel 
  • Doesn’t provide a full picture of users’ decision-making process 

  Last Interaction 

  Last Interaction attribution model (also known as last touch) shifts the entire credit allocation to the last channel before conversion. But it doesn’t account for the contribution of all other channels. 

  If your focus is conversion optimization, the last-touch model helps you determine which channels, assets or campaigns seal the deal for the prospect. 

  Pros 

  • Reports bottom-of-the-funnel events
  • Requires minimal data and configurations 
  • Helps estimate cost-per-lead or cost-per-acquisition

  Cons 

  • No visibility into assisted conversions and prior visitor interactions 
  • Overemphasise the importance of the last channel (which can often be direct traffic) 

  Last Non-Direct Interaction 

  Last Non-Direct attribution excludes direct traffic from the calculation and assigns the full conversion credit to the preceding channel. For example, a paid ad will receive 100% of credit for conversion if a visitor goes directly to your website to buy a product. 

  Last Non-Direct attribution provides greater clarity into the bottom-of-the-funnel (BoFU). events. Yet, it still under-reports the role other channels played in conversion. 

  Pros 

  • Improved channel visibility, compared to Last-Touch 
  • Avoids over-valuing direct visits
  • Reports on lead-generation efforts

  Cons 

  • Doesn’t work for account-based marketing (ABM) 
  • Devalues the quality over quantity of leads 

  Linear Model

  Linear attribution model assigns equal credit for a conversion to all tracked touchpoints, regardless of their impact on the visitor’s decision to convert.

  It helps you understand the full conversion path. But this model doesn’t distinguish between the importance of lead generation activities versus nurturing touches.

  Pros 

  • Focuses on all touch points associated with a conversion 
  • Reflects more steps in the customer journey 
  • Helps analyse longer sales cycles

  Cons 

  • Doesn’t accurately reflect the varying roles of each touchpoint 
  • Can dilute the credit if too many touchpoints are involved 

  Time Decay Model 

  Time decay models assumes that the closer a touchpoint is to the conversion, the greater its influence. Pre-conversion touchpoints get the highest credit, while the first ones are ranked lower (5%-5%-10%-15%-25%-30%).

  This model better reflects real-life customer journeys. However, it devalues the impact of brand awareness and demand-generation campaigns. 

  Pros 

  • Helps track longer sales cycles and reports on each touchpoint involved 
  • Allows customising the half-life of decay to improve reporting 
  • Promotes conversion optimization at BoFu stages

  Cons 

  • Can prompt marketers to curtail ToFU spending, which would translate to fewer qualified leads at lower stages
  • Doesn’t reflect highly-influential events at earlier stages (e.g., a product demo request or free account registration, which didn’t immediately lead to conversion)

  Position-Based Model 

  Position-Based attribution model (also known as the U-shaped model) allocates the biggest credit to the first and the last interaction (40% each). Then distributes the remaining 20% across other touches. 

  For many marketers, that’s the preferred multi-touch attribution model as it allows optimising both ToFU and BoFU channels. 

  Pros 

  • Helps establish the main channels for lead generation and conversion
  • Adds extra layers of visibility, compared to first- and last-touch attribution models 
  • Promotes budget allocation toward the most strategic touchpoints

  Cons 

  • Diminishes the importance of lead nurturing activities as more credit gets assigned to demand-gen and conversion-generation channels
  • Limited flexibility since it always assigns a fixed amount of credit to the first and last touchpoints, and the remaining credit is divided evenly among the other touchpoints

  How to Choose the Right Multi-Touch Attribution Model For Your Business 

  If you’re deciding which attribution model is best for your business, prepare for a heated discussion. Each one has its trade-offs as it emphasises or devalues the role of different channels and marketing activities.

  To reach a consensus, the best strategy is to evaluate each model against three criteria : Your marketing objectives, sales cycle length and data availability. 

  Marketing Objectives 

  Businesses generate revenue in many ways : Through direct sales, subscriptions, referral fees, licensing agreements, one-off or retainer services. Or any combination of these activities. 

  In each case, your marketing strategy will look different. For example, SaaS and direct-to-consumer (DTC) eCommerce brands have to maximise both demand generation and conversion rates. In contrast, a B2B cybersecurity consulting firm is more interested in attracting qualified leads (as opposed to any type of traffic) and progressively nurturing them towards a big-ticket purchase. 

  When selecting a multi-touch attribution model, prioritise your objectives first. Create a simple scoreboard, where your team ranks various channels and campaign types you rely on to close sales. 

  Alternatively, you can survey your customers to learn how they first heard about your company and what eventually triggered their conversion. Having data from both sides can help you cross-validate your assumptions and eliminate some biases. 

  Then consider which model would best reflect the role and importance of different channels in your sales cycle. Speaking of which….

  Sales Cycle Length 

  As shoppers, we spend less time deciding on a new toothpaste brand versus contemplating a new IT system purchase. Factors like industry, business model (B2C, DTC, B2B, B2BC), and deal size determine the average cycle length in your industry. 

  Statistically, low-ticket B2C sales can happen within just several interactions. The average B2B decision-making process can have over 15 steps, spread over several months. 

  That’s why not all multi-touch attribution models work equally well for each business. Time-decay suits better B2B companies, while B2C usually go for position-based or linear attribution. 

  Data Availability 

  Businesses struggle with multi-touch attribution model implementation due to incomplete analytics data. 

  Our web analytics tool captures more data than Google Analytics. That’s because we rely on a privacy-focused tracking mechanism, which allows you to collect analytics without showing a cookie consent banner in markets outside of Germany and the UK. 

  Cookie consent banners are mandatory with Google Analytics. Yet, almost 40% of global consumers reject it. This results in gaps in your analytics and subsequent inconsistencies in multi-touch attribution reports. With Matomo, you can compliantly collect more data for accurate reporting. 

  Some companies also struggle to connect collected insights to individual shoppers. With Matomo, you can cross-attribute users across browning sessions, using our visitors’ tracking feature. 

  When you already know a user’s identifier (e.g., full name or email address), you can track their on-site behaviours over time to better understand how they interact with your content and complete their purchases. Quick disclaimer, though, visitors’ tracking may not be considered compliant with certain data privacy laws. Please consult with a local authority if you have doubts. 

  How to Implement Multi-Touch Attribution

  Multi-touch attribution modelling implementation is like a “seek and find” game. You have to identify all significant touchpoints in your customers’ journeys. And sometimes also brainstorm new ways to uncover the missing parts. Then figure out the best way to track users’ actions at those stages (aka do conversion and events tracking). 

  Here’s a step-by-step walkthrough to help you get started. 

  Select a Multi-Touch Attribution Tool 

  The global marketing attribution software is worth $3.1 billion. Meaning there are plenty of tools, differing in terms of accuracy, sophistication and price.

  To make the right call prioritise five factors :

  • Available models : Look for a solution that offers multiple options and allows you to experiment with different modelling techniques or develop custom models. 
  • Implementation complexity : Some providers offer advanced data modelling tools for creating custom multi-touch attribution models, but offer few out-of-the-box modelling options. 
  • Accuracy : Check if the shortlisted tool collects the type of data you need. Prioritise providers who are less dependent on third-party cookies and allow you to identify repeat users. 
  • Your marketing stack : Some marketing attribution tools come with useful add-ons such as tag manager, heatmaps, form analytics, user session recordings and A/B testing tools. This means you can collect more data for multi-channel modelling with them instead of investing in extra software. 
  • Compliance : Ensure that the selected multi-attribution analytics software wouldn’t put you at risk of GDPR non-compliance when it comes to user privacy and consent to tracking/analysis. 

  Finally, evaluate the adoption costs. Free multi-channel analytics tools come with data quality and consistency trade-offs. Premium attribution tools may have “hidden” licensing costs and bill you for extra data integrations. 

  Look for a tool that offers a good price-to-value ratio (i.e., one that offers extra perks for a transparent price). 

  Set Up Proper Data Collection 

  Multi-touch attribution requires ample user data. To collect the right type of insights you need to set up : 

  • Website analytics : Ensure that you have all tracking codes installed (and working correctly !) to capture pageviews, on-site actions, referral sources and other data points around what users do on page. 
  • Tags : Add tracking parameters to monitor different referral channels (e.g., “facebook”), campaign types (e.g., ”final-sale”), and creative assets (e.g., “banner-1”). Tags help you get a clearer picture of different touchpoints. 
  • Integrations : To better identify on-site users and track their actions, you can also populate your attribution tool with data from your other tools – CRM system, A/B testing app, etc. 

  Finally, think about the ideal lookback window — a bounded time frame you’ll use to calculate conversions. For example, Matomo has a default windows of 7, 30 or 90 days. But you can configure a custom period to better reflect your average sales cycle. For instance, if you’re selling makeup, a shorter window could yield better results. But if you’re selling CRM software for the manufacturing industry, consider extending it.

  Configure Goals and Events 

  Goals indicate your main marketing objectives — more traffic, conversions and sales. In web analytics tools, you can measure these by tracking specific user behaviours. 

  For example : If your goal is lead generation, you can track :

  • Newsletter sign ups 
  • Product demo requests 
  • Gated content downloads 
  • Free trial account registration 
  • Contact form submission 
  • On-site call bookings 

  In each case, you can set up a unique tag to monitor these types of requests. Then analyse conversion rates — the percentage of users who have successfully completed the action. 

  To collect sufficient data for multi-channel attribution modelling, set up Goal Tracking for different types of touchpoints (MoFU & BoFU) and asset types (contact forms, downloadable assets, etc). 

  Your next task is to figure out how users interact with different on-site assets. That’s when Event Tracking comes in handy. 

  Event Tracking reports notify you about specific actions users take on your website. With Matomo Event Tracking, you can monitor where people click on your website, on which pages they click newsletter subscription links, or when they try to interact with static content elements (e.g., a non-clickable banner). 

  Using in-depth user behavioural reports, you can better understand which assets play a key role in the average customer journey. Using this data, you can localise “leaks” in your sales funnel and fix them to increase conversion rates.

  Test and Validated the Selected Model 

  A common challenge of multi-channel attribution modelling is determining the correct correlation and causality between exposure to touchpoints and purchases. 

  For example, a user who bought a discounted product from a Facebook ad would act differently than someone who purchased a full-priced product via a newsletter link. Their rate of pre- and post-sales exposure will also differ a lot — and your attribution model may not always accurately capture that. 

  That’s why you have to continuously test and tweak the selected model type. The best approach for that is lift analysis. 

  Lift analysis means comparing how your key metrics (e.g., revenue or conversion rates) change among users who were exposed to a certain campaign versus a control group. 

  In the case of multi-touch attribution modelling, you have to monitor how your metrics change after you’ve acted on the model recommendations (e.g., invested more in a well-performing referral channel or tried a new brand awareness Twitter ad). Compare the before and after ROI. If you see a positive dynamic, your model works great. 

  The downside of this approach is that you have to invest a lot upfront. But if your goal is to create a trustworthy attribution model, the best way to validate is to act on its suggestions and then test them against past results. 

  Conclusion

  A multi-touch attribution model helps you measure the impact of different channels, campaign types, and marketing assets on metrics that matter — conversion rate, sales volumes and ROI. 

  Using this data, you can invest budgets into the best-performing channels and confidently experiment with new campaign types. 

  As a Matomo user, you also get to do so without breaching customers’ privacy or compromising on analytics accuracy.

  Start using accurate multi-channel attribution in Matomo. Get your free 21-day trial now. No credit card required.

• FFmpeg smearing rtp missed packet

  3 janvier 2018, par Akim Benchiha

  I’m using ffmpeg to combine streams. But during the combinaison I have some errors/Warnings. I don’t know why. I can see the frames are dropping. And the output video is poor quality

  Here the situation :
  First : Try to combine local video and a rtsp stream from data center.

  ffmpeg -i rtsp://cloudzensg.loginto.me:554/livecast -i Xmen2trailer.mov -filter_complex "[0]scale=-1:-1[b];[1]scale=128:128[w];[b][w] overlay=10:10" -vcodec libx264 -preset ultrafast -f flv out.mp4
  
  ffmpeg version N-89672-g41e51fbcd9 Copyright (c) 2000-2018 the FFmpeg developers
  
    built with gcc 7.2.0 (GCC)
  
  [udp @ 000001e07f58ccc0] 'circular_buffer_size' option was set but it is not supported on this build (pthread support is required)
  
  [udp @ 000001e07f5a2b80] 'circular_buffer_size' option was set but it is not supported on this build (pthread support is required)
  
  [udp @ 000001e07f5b4040] 'circular_buffer_size' option was set but it is not supported on this build (pthread support is required)
  
  [udp @ 000001e07f5c4300] 'circular_buffer_size' option was set but it is not supported on this build (pthread support is required)
  
  Input #0, rtsp, from 'rtsp://cloudzensg.loginto.me:554/livecast':
  
    Metadata:
  
      title           : session
  
    Duration: N/A, start: 0.086367, bitrate: N/A
  
      Stream #0:0: Audio: aac, 44100 Hz, stereo, fltp
  
      Stream #0:1: Video: h264 (Constrained Baseline), yuv420p(progressive), 1280x720, 30 fps, 30 tbr, 90k tbn, 60 tbc
  
  Input #1, mov,mp4,m4a,3gp,3g2,mj2, from 'Xmen2trailer.mov':
  
    Metadata:
  
      creation_time   : 2003-02-17T16:23:00.000000Z
  
      title           : X2
  
      title-eng       : X2
  
      copyright-eng   : ┬⌐2003 20th Century Fox
  
      comment         : QuickTime 5 version encoded and delivered by www.apple.com/trailers/
  
      copyright       : ┬⌐2003 20th Century Fox
  
      comment-eng     : QuickTime 5 version encoded and delivered by www.apple.com/trailers/
  
    Duration: 00:02:29.08, start: 0.000000, bitrate: 1283 kb/s
  
      Stream #1:0(eng): Video: svq3 (SVQ3 / 0x33515653), yuvj420p(pc), 480x272, 1153 kb/s, 24 fps, 24 tbr, 600 tbn, 600 tbc (default)
  
      Metadata:
  
        creation_time   : 2003-02-17T16:23:00.000000Z
  
        handler_name    : Apple Alias Data Handler
  
        encoder         : Sorenson Video 3
  
      Stream #1:1(eng): Audio: qdm2 (QDM2 / 0x324D4451), 44100 Hz, stereo, s16, 128 kb/s (default)
  
      Metadata:
  
        creation_time   : 2003-02-17T16:23:00.000000Z
  
        handler_name    : Apple Alias Data Handler
  
  File 'out.mp4' already exists. Overwrite ? [y/N] y
  
  Stream mapping:
  
    Stream #0:1 (h264) -> scale (graph 0)
  
    Stream #1:0 (svq3) -> scale (graph 0)
  
    overlay (graph 0) -> Stream #0:0 (libx264)
  
    Stream #1:1 -> #0:1 (qdm2 (native) -> mp3 (libmp3lame))
  
  Press [q] to stop, [?] for help
  
  [swscaler @ 000001e002b3d980] deprecated pixel format used, make sure you did set range correctly
  
  [libx264 @ 000001e07f5edd00] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2
  
  [libx264 @ 000001e07f5edd00] profile Constrained Baseline, level 3.1
  
  [libx264 @ 000001e07f5edd00] 264 - core 152 r2851 ba24899 - H.264/MPEG-4 AVC codec - Copyleft 2003-2017 - http://www.videolan.org/x264.html - options: cabac=0 ref=1 deblock=0:0:0 analyse=0:0 me=dia subme=0 psy=1 psy_rd=1.00:0.00 mixed_ref=0 me_range=16 chroma_me=1 trellis=0 8x8dct=0 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=0 threads=12 lookahead_threads=2 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=0 weightp=0 keyint=250 keyint_min=25 scenecut=0 intra_refresh=0 rc=crf mbtree=0 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=0
  
  Output #0, flv, to 'out.mp4':
  
    Metadata:
  
      title           : session
  
      encoder         : Lavf58.3.100
  
      Stream #0:0: Video: h264 (libx264) ([7][0][0][0] / 0x0007), yuv420p, 1280x720, q=-1--1, 30 fps, 1k tbn, 30 tbc (default)
  
      Metadata:
  
        encoder         : Lavc58.9.100 libx264
  
      Side data:
  
        cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: -1
  
      Stream #0:1(eng): Audio: mp3 (libmp3lame) ([2][0][0][0] / 0x0002), 44100 Hz, stereo, s16p (default)
  
      Metadata:
  
        creation_time   : 2003-02-17T16:23:00.000000Z
  
        handler_name    : Apple Alias Data Handler
  
        encoder         : Lavc58.9.100 libmp3lame
  
  Past duration 0.889320 too large
  
  Past duration 0.629326 too large
  
  Past duration 0.979652 too large
  
  Past duration 0.909660 too large
  
  Past duration 0.646996 too large
  
  Past duration 0.881325 too large
  
  Past duration 0.728661 too large
  
  Past duration 0.970665 too large
  
  Past duration 0.610664 too large
  
  Past duration 0.851997 too large
  
  Past duration 0.779991 too large
  
  Past duration 0.870995 too large
  
  Past duration 0.752327 too large
  
  Past duration 0.970665 too large
  
  Past duration 0.679665 too large
  
  Past duration 0.951988 too large
  
  Past duration 0.913994 too large
  
  Past duration 0.641655 too large
  
  [rtsp @ 000001e07f58a700] max delay reached. need to consume packet
  
  [rtsp @ 000001e07f58a700] RTP: missed 747 packets
  
  [h264 @ 000001e07f63a140] corrupted macroblock 30 15 (total_coeff=-1)063.3kbits/s dup=0 drop=66 speed=6.52x
  
  [h264 @ 000001e07f63a140] error while decoding MB 30 15
  
  [h264 @ 000001e07f63a140] concealing 2380 DC, 2380 AC, 2380 MV errors in P frame
  
  Past duration 0.971657 too large
  
  Past duration 0.867989 too large    1280kB time=00:00:04.44 bitrate=2360.6kbits/s dup=0 drop=70 speed=1.44x
  
  [rtsp @ 000001e07f58a700] max delay reached. need to consume packet
  
  [rtsp @ 000001e07f58a700] RTP: missed 43 packets
  
  [h264 @ 000001e07f639380] corrupted macroblock 11 18 (total_coeff=-1)
  
  [h264 @ 000001e07f639380] error while decoding MB 11 18
  
  [h264 @ 000001e07f639380] concealing 2156 DC, 2156 AC, 2156 MV errors in P frame
  
  Past duration 0.895988 too large
  
  Past duration 0.708656 too large
  
  frame=  105 fps= 29 q=-1.0 Lsize=    2169kB time=00:00:08.98 bitrate=1977.1kbits/s dup=0 drop=76 speed=2.52x
  
  video:2020kB audio:141kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.363079%
  
  [libx264 @ 000001e07f5edd00] frame I:1     Avg QP:20.00  size: 84510
  
  [libx264 @ 000001e07f5edd00] frame P:104   Avg QP:18.44  size: 19074
  
  [libx264 @ 000001e07f5edd00] mb I  I16..4: 100.0%  0.0%  0.0%
  
  [libx264 @ 000001e07f5edd00] mb P  I16..4: 15.4%  0.0%  0.0%  P16..4: 23.1%  0.0%  0.0%  0.0%  0.0%    skip:61.5%
  
  [libx264 @ 000001e07f5edd00] coded y,uvDC,uvAC intra: 7.4% 7.3% 4.5% inter: 14.3% 12.2% 3.4%
  
  [libx264 @ 000001e07f5edd00] i16 v,h,dc,p: 71% 27%  1%  0%
  
  [libx264 @ 000001e07f5edd00] i8c dc,h,v,p: 58% 37%  4%  0%
  
  [libx264 @ 000001e07f5edd00] kb/s:1969.74
  
  Exiting normally, received signal 2

  second :
  Try to combine local rtsp and local video

  ffmpeg -i rtsp://192.168.1.203:554/livecast -i Xmen2trailer.mov -filter_complex "[0]scale=-1:-1[b];[1]scale=128:128[w];[b][w] overlay=10:10" -vcodec libx264 -preset ultrafast -f flv out.mp4
  
  ffmpeg version N-89672-g41e51fbcd9 Copyright (c) 2000-2018 the FFmpeg developers
  
    built with gcc 7.2.0 (GCC)
  
  [udp @ 000002aa1fe4ca00] 'circular_buffer_size' option was set but it is not supported on this build (pthread support is required)
  
  [udp @ 000002aa1fe62900] 'circular_buffer_size' option was set but it is not supported on this build (pthread support is required)
  
  [udp @ 000002aa1fe73d80] 'circular_buffer_size' option was set but it is not supported on this build (pthread support is required)
  
  [udp @ 000002aa1fe84040] 'circular_buffer_size' option was set but it is not supported on this build (pthread support is required)
  
  Input #0, rtsp, from 'rtsp://192.168.1.203:554/livecast':
  
    Metadata:
  
      title           : session
  
    Duration: N/A, start: 0.000000, bitrate: N/A
  
      Stream #0:0: Audio: aac (LC), 48000 Hz, stereo, fltp
  
      Stream #0:1: Video: h264 (Constrained Baseline), yuv420p(progressive), 1920x1080, 30 fps, 30 tbr, 90k tbn, 60 tbc
  
  Input #1, mov,mp4,m4a,3gp,3g2,mj2, from 'Xmen2trailer.mov':
  
    Metadata:
  
      creation_time   : 2003-02-17T16:23:00.000000Z
  
      title           : X2
  
      title-eng       : X2
  
      copyright-eng   : ┬⌐2003 20th Century Fox
  
      comment         : QuickTime 5 version encoded and delivered by www.apple.com/trailers/
  
      copyright       : ┬⌐2003 20th Century Fox
  
      comment-eng     : QuickTime 5 version encoded and delivered by www.apple.com/trailers/
  
    Duration: 00:02:29.08, start: 0.000000, bitrate: 1283 kb/s
  
      Stream #1:0(eng): Video: svq3 (SVQ3 / 0x33515653), yuvj420p(pc), 480x272, 1153 kb/s, 24 fps, 24 tbr, 600 tbn, 600 tbc (default)
  
      Metadata:
  
        creation_time   : 2003-02-17T16:23:00.000000Z
  
        handler_name    : Apple Alias Data Handler
  
        encoder         : Sorenson Video 3
  
      Stream #1:1(eng): Audio: qdm2 (QDM2 / 0x324D4451), 44100 Hz, stereo, s16, 128 kb/s (default)
  
      Metadata:
  
        creation_time   : 2003-02-17T16:23:00.000000Z
  
        handler_name    : Apple Alias Data Handler
  
  File 'out.mp4' already exists. Overwrite ? [y/N] y
  
  Stream mapping:
  
    Stream #0:1 (h264) -> scale (graph 0)
  
    Stream #1:0 (svq3) -> scale (graph 0)
  
    overlay (graph 0) -> Stream #0:0 (libx264)
  
    Stream #0:0 -> #0:1 (aac (native) -> mp3 (libmp3lame))
  
  Press [q] to stop, [?] for help
  
  [swscaler @ 000002aa2355ba40] deprecated pixel format used, make sure you did set range correctly
  
  [libx264 @ 000002aa202d9600] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2
  
  [libx264 @ 000002aa202d9600] profile Constrained Baseline, level 4.0
  
  [libx264 @ 000002aa202d9600] 264 - core 152 r2851 ba24899 - H.264/MPEG-4 AVC codec - Copyleft 2003-2017 - http://www.videolan.org/x264.html - options: cabac=0 ref=1 deblock=0:0:0 analyse=0:0 me=dia subme=0 psy=1 psy_rd=1.00:0.00 mixed_ref=0 me_range=16 chroma_me=1 trellis=0 8x8dct=0 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=0 threads=12 lookahead_threads=2 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=0 weightp=0 keyint=250 keyint_min=25 scenecut=0 intra_refresh=0 rc=crf mbtree=0 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=0
  
  Output #0, flv, to 'out.mp4':
  
    Metadata:
  
      title           : session
  
      encoder         : Lavf58.3.100
  
      Stream #0:0: Video: h264 (libx264) ([7][0][0][0] / 0x0007), yuv420p, 1920x1080, q=-1--1, 30 fps, 1k tbn, 30 tbc (default)
  
      Metadata:
  
        encoder         : Lavc58.9.100 libx264
  
      Side data:
  
        cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: -1
  
      Stream #0:1: Audio: mp3 (libmp3lame) ([2][0][0][0] / 0x0002), 48000 Hz, stereo, fltp
  
      Metadata:
  
        encoder         : Lavc58.9.100 libmp3lame
  
  Past duration 0.711662 too large
  
  Past duration 0.822990 too large
  
  Past duration 0.854332 too large
  
  [rtsp @ 000002aa1fe4a680] max delay reached. need to consume packet
  
  [rtsp @ 000002aa1fe4a680] RTP: missed 1315 packets
  
  [h264 @ 000002aa20262580] Invalid level prefix
  
  [h264 @ 000002aa20262580] error while decoding MB 12 37
  
  [h264 @ 000002aa20262580] concealing 3757 DC, 3757 AC, 3757 MV errors in I frame
  
  Past duration 0.732323 too large     256kB time=00:00:02.88 bitrate= 727.2kbits/s dup=0 drop=13 speed=5.76x
  
  Past duration 0.824333 too large
  
  Past duration 0.988991 too large
  
  Past duration 0.862328 too large    1024kB time=00:00:03.38 bitrate=2477.4kbits/s dup=0 drop=21 speed=3.34x
  
  Past duration 0.861320 too large
  
  Past duration 0.883324 too large
  
  Past duration 0.910652 too large    1280kB time=00:00:03.94 bitrate=2659.3kbits/s dup=0 drop=30 speed=2.59x
  
  Past duration 0.954659 too large
  
  Past duration 0.790657 too large    1792kB time=00:00:04.40 bitrate=3335.6kbits/s dup=0 drop=37 speed=2.17x
  
  Past duration 0.861320 too large
  
  Past duration 0.943657 too large
  
  Past duration 0.988655 too large    2304kB time=00:00:04.90 bitrate=3849.6kbits/s dup=0 drop=45 speed=1.94x
  
  Past duration 0.810326 too large
  
  Past duration 0.893654 too large
  
  Past duration 0.822319 too large    3072kB time=00:00:05.40 bitrate=4655.2kbits/s dup=0 drop=53 speed=1.78x
  
  Past duration 0.902657 too large
  
  Past duration 0.909660 too large
  
  Past duration 0.779655 too large    3328kB time=00:00:05.93 bitrate=4596.7kbits/s dup=0 drop=61 speed=1.67x
  
  Past duration 0.957664 too large
  
  Past duration 0.778328 too large    3840kB time=00:00:06.43 bitrate=4890.0kbits/s dup=0 drop=68 speed=1.59x
  
  Past duration 0.861992 too large
  
  Past duration 0.992653 too large
  
  Past duration 0.729652 too large    4352kB time=00:00:06.94 bitrate=5133.4kbits/s dup=0 drop=76 speed=1.53x
  
  [rtsp @ 000002aa1fe4a680] max delay reached. need to consume packet
  
  [rtsp @ 000002aa1fe4a680] RTP: missed 2 packets
  
  Past duration 0.857994 too large
  
  [h264 @ 000002aa20260580] Invalid level prefix
  
  [h264 @ 000002aa20260580] error while decoding MB 43 62
  
  [h264 @ 000002aa20260580] concealing 726 DC, 726 AC, 726 MV errors in P frame
  
  Past duration 0.889000 too large
  
  Past duration 0.800987 too large    4864kB time=00:00:07.42 bitrate=5365.7kbits/s dup=0 drop=83 speed=1.47x
  
  Past duration 0.909660 too large
  
  Past duration 0.946327 too large
  
  Past duration 0.795998 too large
  
  Past duration 0.902321 too large    5376kB time=00:00:07.95 bitrate=5539.0kbits/s dup=0 drop=91 speed=1.43x
  
  Past duration 0.841652 too large
  
  Past duration 0.859657 too large
  
  Past duration 0.992332 too large    5632kB time=00:00:08.43 bitrate=5472.3kbits/s dup=0 drop=99 speed=1.39x
  
  Past duration 0.893990 too large
  
  Past duration 0.947990 too large    6400kB time=00:00:08.95 bitrate=5853.4kbits/s dup=0 drop=106 speed=1.36x
  
  Past duration 0.678322 too large
  
  Past duration 0.994987 too large
  
  Past duration 0.942329 too large
  
  Past duration 0.975319 too large
  
  Past duration 0.702660 too large    6912kB time=00:00:09.45 bitrate=5986.8kbits/s dup=0 drop=114 speed=1.34x
  
  Past duration 0.821663 too large
  
  Past duration 0.937325 too large
  
  Past duration 0.992989 too large
  
  Past duration 0.684990 too large    7168kB time=00:00:09.96 bitrate=5895.0kbits/s dup=0 drop=122 speed=1.31x
  
  Past duration 0.763664 too large
  
  Past duration 0.990318 too large
  
  Past duration 0.921333 too large
  
  Past duration 0.945320 too large
  
  Past duration 0.711327 too large    7680kB time=00:00:10.49 bitrate=5994.1kbits/s dup=0 drop=130 speed=1.29x
  
  Past duration 0.841652 too large
  
  Past duration 0.948997 too large
  
  Past duration 0.994652 too large
  
  Past duration 0.759987 too large    8448kB time=00:00:11.04 bitrate=6267.0kbits/s dup=0 drop=138 speed=1.28x
  
  Past duration 0.860985 too large
  
  Past duration 0.984993 too large
  
  Past duration 0.796989 too large    8960kB time=00:00:11.50 bitrate=6382.1kbits/s dup=0 drop=145 speed=1.26x
  
  Past duration 0.914665 too large
  
  Past duration 0.804329 too large    9472kB time=00:00:12.02 bitrate=6452.2kbits/s dup=0 drop=152 speed=1.25x
  
  frame=  303 fps= 31 q=-1.0 Lsize=   10246kB time=00:00:12.33 bitrate=6803.2kbits/s dup=0 drop=156 speed=1.25x
  
  video:10039kB audio:193kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.140463%
  
  [libx264 @ 000002aa202d9600] frame I:2     Avg QP:18.00  size:199681
  
  [libx264 @ 000002aa202d9600] frame P:301   Avg QP:18.96  size: 32823
  
  [libx264 @ 000002aa202d9600] mb I  I16..4: 100.0%  0.0%  0.0%
  
  [libx264 @ 000002aa202d9600] mb P  I16..4:  9.3%  0.0%  0.0%  P16..4: 32.1%  0.0%  0.0%  0.0%  0.0%    skip:58.6%
  
  [libx264 @ 000002aa202d9600] coded y,uvDC,uvAC intra: 12.9% 34.0% 11.0% inter: 12.0% 22.7% 6.2%
  
  [libx264 @ 000002aa202d9600] i16 v,h,dc,p: 38% 49%  9%  4%
  
  [libx264 @ 000002aa202d9600] i8c dc,h,v,p: 38% 42% 14%  6%
  
  [libx264 @ 000002aa202d9600] kb/s:6833.78
  
  Exiting normally, received signal 2.

  third :
  Combine RTMP from phone and RTSP video from server

  ffmpeg -i rtsp://192.168.1.203:554/livecast -i rtmp://192.168.1.152:1935/ingest/test -filter_complex "[0]scale=-1:-1[b];[1]scale=200:200[w];[b][w] overlay=10:10" -c:v libx264 -preset ultrafast -f flv outputRTMP.mp4
  
  ffmpeg version N-89672-g41e51fbcd9 Copyright (c) 2000-2018 the FFmpeg developers
  
    built with gcc 7.2.0 (GCC)
  
    configuration: --enable-gpl --enable-version3 --enable-sdl2 --enable-bzlib --enable-fontconfig --enable-gnutls --enable-iconv --enable-libass --enable-libbluray --enable-libfreetype --enable-libmp3lame --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-libopus --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libtheora --enable-libtwolame --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libzimg --enable-lzma --enable-zlib --enable-gmp --enable-libvidstab --enable-libvorbis --enable-libvo-amrwbenc --enable-libmysofa --enable-libspeex --enable-amf --enable-cuda --enable-cuvid --enable-d3d11va --enable-nvenc --enable-dxva2 --enable-avisynth --enable-libmfx
  
    libavutil      56.  7.100 / 56.  7.100
  
    libavcodec     58.  9.100 / 58.  9.100
  
    libavformat    58.  3.100 / 58.  3.100
  
    libavdevice    58.  0.100 / 58.  0.100
  
    libavfilter     7.  8.100 /  7.  8.100
  
    libswscale      5.  0.101 /  5.  0.101
  
    libswresample   3.  0.101 /  3.  0.101
  
    libpostproc    55.  0.100 / 55.  0.100
  
  [udp @ 0000018c0ccbca40] 'circular_buffer_size' option was set but it is not supported on this build (pthread support is required)
  
  [udp @ 0000018c0ccd2900] 'circular_buffer_size' option was set but it is not supported on this build (pthread support is required)
  
  [udp @ 0000018c0cce3dc0] 'circular_buffer_size' option was set but it is not supported on this build (pthread support is required)
  
  [udp @ 0000018c0ccf4080] 'circular_buffer_size' option was set but it is not supported on this build (pthread support is required)
  
  Input #0, rtsp, from 'rtsp://192.168.1.203:554/livecast':
  
    Metadata:
  
      title           : session
  
    Duration: N/A, start: 0.000000, bitrate: N/A
  
      Stream #0:0: Audio: aac (LC), 48000 Hz, stereo, fltp
  
      Stream #0:1: Video: h264 (Constrained Baseline), yuv420p(progressive), 1920x1080, 30 fps, 30 tbr, 90k tbn, 60 tbc
  
  Input #1, flv, from 'rtmp://192.168.1.152:1935/ingest/test':
  
    Metadata:
  
      Server          : NGINX RTMP (github.com/arut/nginx-rtmp-module)
  
      displayWidth    : 640
  
      displayHeight   : 480
  
      fps             : 0
  
      profile         :
  
      level           :
  
    Duration: 00:00:00.00, start: 173.197000, bitrate: N/A
  
      Stream #1:0: Audio: aac (LC), 44100 Hz, mono, fltp, 47 kb/s
  
      Stream #1:1: Video: h264 (Baseline), yuv420p(tv, smpte170m/bt470bg/smpte170m, progressive), 640x480, 1999 kb/s, 29.92 fps, 29.92 tbr, 1k tbn
  
  File 'outputRTMP.mp4' already exists. Overwrite ? [y/N] y
  
  Stream mapping:
  
    Stream #0:1 (h264) -> scale (graph 0)
  
    Stream #1:1 (h264) -> scale (graph 0)
  
    overlay (graph 0) -> Stream #0:0 (libx264)
  
    Stream #0:0 -> #0:1 (aac (native) -> mp3 (libmp3lame))
  
  Press [q] to stop, [?] for help
  
  [libx264 @ 0000018c0d1321c0] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2
  
  [libx264 @ 0000018c0d1321c0] profile Constrained Baseline, level 4.0
  
  [libx264 @ 0000018c0d1321c0] 264 - core 152 r2851 ba24899 - H.264/MPEG-4 AVC codec - Copyleft 2003-2017 - http://www.videolan.org/x264.html - options: cabac=0 ref=1 deblock=0:0:0 analyse=0:0 me=dia subme=0 psy=1 psy_rd=1.00:0.00 mixed_ref=0 me_range=16 chroma_me=1 trellis=0 8x8dct=0 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=0 threads=12 lookahead_threads=2 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=0 weightp=0 keyint=250 keyint_min=25 scenecut=0 intra_refresh=0 rc=crf mbtree=0 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=0
  
  Output #0, flv, to 'outputRTMP.mp4':
  
    Metadata:
  
      title           : session
  
      encoder         : Lavf58.3.100
  
      Stream #0:0: Video: h264 (libx264) ([7][0][0][0] / 0x0007), yuv420p, 1920x1080, q=-1--1, 30 fps, 1k tbn, 30 tbc (default)
  
      Metadata:
  
        encoder         : Lavc58.9.100 libx264
  
      Side data:
  
        cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: -1
  
      Stream #0:1: Audio: mp3 (libmp3lame) ([2][0][0][0] / 0x0002), 48000 Hz, stereo, fltp
  
      Metadata:
  
        encoder         : Lavc58.9.100 libmp3lame
  
  Past duration 0.931999 too large
  
  [rtsp @ 0000018c0ccba6c0] max delay reached. need to consume packet
  
  [rtsp @ 0000018c0ccba6c0] RTP: missed 92 packets
  
  [rtsp @ 0000018c0ccba6c0] max delay reached. need to consume packet
  
  [rtsp @ 0000018c0ccba6c0] RTP: missed 2904 packets
  
  Past duration 0.671654 too large
  
  [h264 @ 0000018c0d0da140] concealing 4160 DC, 4160 AC, 4160 MV errors in I frame
  
  Past duration 0.991997 too large
  
  Past duration 0.791328 too large     256kB time=00:00:05.12 bitrate= 409.3kbits/s dup=0 drop=12 speed=4.14x
  
  Past duration 0.969994 too large
  
  [rtsp @ 0000018c0ccba6c0] max delay reached. need to consume packet
  
  [rtsp @ 0000018c0ccba6c0] RTP: missed 573 packets
  
  [h264 @ 0000018c0d0d8a80] concealing 2468 DC, 2468 AC, 2468 MV errors in P frame
  
  Past duration 0.670326 too large
  
  [rtsp @ 0000018c0ccba6c0] max delay reached. need to consume packet
  
  [rtsp @ 0000018c0ccba6c0] RTP: missed 25 packets
  
  [h264 @ 0000018c0d0d8a80] concealing 6479 DC, 6479 AC, 6479 MV errors in P frame
  
  Past duration 0.961327 too large     512kB time=00:00:11.10 bitrate= 377.7kbits/s dup=0 drop=16 speed=1.57x
  
  Past duration 0.689323 too large
  
  [rtsp @ 0000018c0ccba6c0] max delay reached. need to consume packet
  
  [rtsp @ 0000018c0ccba6c0] RTP: missed 620 packets
  
  [h264 @ 0000018c0d0da140] negative number of zero coeffs at 33 32
  
  [h264 @ 0000018c0d0da140] error while decoding MB 33 32
  
  [h264 @ 0000018c0d0da140] concealing 4336 DC, 4336 AC, 4336 MV errors in P frame
  
  Past duration 0.790321 too large
  
  Past duration 0.910332 too large     768kB time=00:00:12.23 bitrate= 514.3kbits/s dup=0 drop=18 speed=1.62x
  
  [rtsp @ 0000018c0ccba6c0] max delay reached. need to consume packet
  
  [rtsp @ 0000018c0ccba6c0] RTP: missed 24 packets
  
  [h264 @ 0000018c0d0da140] corrupted macroblock 22 25 (total_coeff=-1)
  
  [h264 @ 0000018c0d0da140] error while decoding MB 22 25
  
  [h264 @ 0000018c0d0da140] concealing 5151 DC, 5151 AC, 5151 MV errors in P frame
  
  Past duration 0.924324 too large    1024kB time=00:00:17.03 bitrate= 492.5kbits/s dup=0 drop=19 speed= 1.3x
  
  Past duration 0.656654 too large
  
  [rtsp @ 0000018c0ccba6c0] max delay reached. need to consume packet
  
  [rtsp @ 0000018c0ccba6c0] RTP: missed 516 packets
  
  [h264 @ 0000018c0d0daf00] Invalid level prefix
  
  [h264 @ 0000018c0d0daf00] error while decoding MB 0 36
  
  [h264 @ 0000018c0d0daf00] concealing 3889 DC, 3889 AC, 3889 MV errors in P frame
  
  [rtsp @ 0000018c0ccba6c0] max delay reached. need to consume packet
  
  [rtsp @ 0000018c0ccba6c0] RTP: missed 132 packets
  
  [h264 @ 0000018c0d0d8a80] top block unavailable for requested intra mode -1
  
  [h264 @ 0000018c0d0d8a80] error while decoding MB 55 26
  
  [h264 @ 0000018c0d0d8a80] concealing 5034 DC, 5034 AC, 5034 MV errors in I frame
  
  [h264 @ 0000018c0d0d9cc0] concealing 2621 DC, 2621 AC, 2621 MV errors in P frame
  
  Past duration 0.935661 too large
  
  Past duration 0.878319 too large
  
  Past duration 0.929329 too large    1280kB time=00:00:18.32 bitrate= 572.1kbits/s dup=0 drop=22 speed=1.27x
  
  [rtsp @ 0000018c0ccba6c0] max delay reached. need to consume packet
  
  [rtsp @ 0000018c0ccba6c0] RTP: missed 560 packets
  
  [h264 @ 0000018c0d0d8140] Invalid level prefix
  
  Past duration 0.661659 too large
  
  [h264 @ 0000018c0d0d8140] error while decoding MB 91 24
  
  [h264 @ 0000018c0d0d8140] concealing 5214 DC, 5214 AC, 5214 MV errors in P frame
  
  Past duration 0.823662 too large
  
  Past duration 0.864662 too large
  
  [rtsp @ 0000018c0ccba6c0] max delay reached. need to consume packet
  
  [rtsp @ 0000018c0ccba6c0] RTP: missed 29 packets
  
  [h264 @ 0000018c0d0d8140] corrupted macroblock 42 3 (total_coeff=-1)
  
  [h264 @ 0000018c0d0d8140] error while decoding MB 42 3
  
  [h264 @ 0000018c0d0d8140] concealing 7760 DC, 7760 AC, 7760 MV errors in P frame
  
  Past duration 0.780663 too large    1792kB time=00:00:19.50 bitrate= 752.8kbits/s dup=0 drop=24 speed=1.27x
  
  Past duration 0.900322 too large
  
  Past duration 0.990990 too large
  
  [rtsp @ 0000018c0ccba6c0] max delay reached. need to consume packet
  
  [rtsp @ 0000018c0ccba6c0] RTP: missed 565 packets
  
  [h264 @ 0000018c0d0d8140] corrupted macroblock 83 27 (total_coeff=-1)
  
  [h264 @ 0000018c0d0d8140] Past duration 0.862999 too large
  
  error while decoding MB 83 27
  
  [h264 @ 0000018c0d0d8140] concealing 4866 DC, 4866 AC, 4866 MV errors in P frame
  
  [rtsp @ 0000018c0ccba6c0] max delay reached. need to consume packet
  
  [rtsp @ 0000018c0ccba6c0] RTP: missed 7 packets
  
  [h264 @ 0000018c0d0d8f00] top block unavailable for requested intra mode
  
  [h264 @ 0000018c0d0d8f00] error while decoding MB 79 16
  
  [h264 @ 0000018c0d0d8f00] concealing 2661 DC, 2661 AC, 2661 MV errors in P frame
  
  Past duration 0.907997 too large
  
  [rtsp @ 0000018c0ccba6c0] max delay reached. need to consume packet= 816.0kbits/s dup=0 drop=28 speed=1.29x
  
  [rtsp @ 0000018c0ccba6c0] RTP: missed 19 packets
  
  [h264 @ 0000018c0d0d9cc0] corrupted macroblock 88 59 (total_coeff=-1)
  
  [h264 @ 0000018c0d0d9cc0] error while decoding MB 88 59
  
  [h264 @ 0000018c0d0d9cc0] concealing 1041 DC, 1041 AC, 1041 MV errors in P frame
  
  [rtsp @ 0000018c0ccba6c0] max delay reached. need to consume packet
  
  [rtsp @ 0000018c0ccba6c0] RTP: missed 6 packets
  
  [h264 @ 0000018c0d0d8140] out of range intra chroma pred mode
  
  [h264 @ 0000018c0d0d8140] error while decoding MB 118 6
  
  [h264 @ 0000018c0d0d8140] concealing 3320 DC, 3320 AC, 3320 MV errors in P frame
  
  Past duration 0.845665 too large    2304kB time=00:00:20.72 bitrate= 910.6kbits/s dup=0 drop=29 speed=1.23x
  
  [rtsp @ 0000018c0ccba6c0] max delay reached. need to consume packet
  
  [rtsp @ 0000018c0ccba6c0] RTP: missed 574 packets
  
  [h264 @ 0000018c0d0d8140] negative number of zero coeffs at 39 26
  
  [h264 @ 0000018c0d0d8140] error while decoding MB 39 26
  
  [h264 @ 0000018c0d0d8140] concealing 5050 DC, 5050 AC, 5050 MV errors in P frame
  
  Past duration 0.950996 too large
  
  [rtsp @ 0000018c0ccba6c0] max delay reached. need to consume packet
  
  [rtsp @ 0000018c0ccba6c0] RTP: missed 37 packets
  
  [h264 @ 0000018c0d0d8140] corrupted macroblock 48 37 (total_coeff=-1)
  
  [h264 @ 0000018c0d0d8140] error while decoding MB 48 37
  
  [h264 @ 0000018c0d0d8140] concealing 3721 DC, 3721 AC, 3721 MV errors in P frame
  
  Past duration 0.789330 too large    2816kB time=00:00:22.02 bitrate=1047.5kbits/s dup=0 drop=33 speed=1.23x
  
  Past duration 0.848320 too large
  
  [rtsp @ 0000018c0ccba6c0] max delay reached. need to consume packet
  
  [rtsp @ 0000018c0ccba6c0] RTP: missed 581 packets
  
  [h264 @ 0000018c0d0d8f00] corrupted macroblock 13 10 (total_coeff=-1)
  
  [h264 @ 0000018c0d0d8f00] error while decoding MB 13 10
  
  Past duration 0.875664 too large
  
  [h264 @ 0000018c0d0d8f00] concealing 6952 DC, 6952 AC, 6952 MV errors in P frame
  
  [rtsp @ 0000018c0ccba6c0] max delay reached. need to consume packet=1181.0kbits/s dup=0 drop=35 speed=1.25x
  
  [rtsp @ 0000018c0ccba6c0] RTP: missed 6 packets
  
  [h264 @ 0000018c0d0d8f00] corrupted macroblock 72 37 (total_coeff=-1)
  
  [h264 @ 0000018c0d0d8f00] error while decoding MB 72 37
  
  [h264 @ 0000018c0d0d8f00] concealing 3675 DC, 3675 AC, 3675 MV errors in P frame
  
  frame=  101 fps=5.3 q=-1.0 Lsize=    4095kB time=00:00:23.67 bitrate=1417.0kbits/s dup=0 drop=37 speed=1.25x
  
  video:3739kB audio:340kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.405426%
  
  [libx264 @ 0000018c0d1321c0] frame I:1     Avg QP:20.00  size:178581
  
  [libx264 @ 0000018c0d1321c0] frame P:100   Avg QP:20.42  size: 36495
  
  [libx264 @ 0000018c0d1321c0] mb I  I16..4: 100.0%  0.0%  0.0%
  
  [libx264 @ 0000018c0d1321c0] mb P  I16..4: 11.8%  0.0%  0.0%  P16..4: 31.7%  0.0%  0.0%  0.0%  0.0%    skip:56.5%
  
  [libx264 @ 0000018c0d1321c0] coded y,uvDC,uvAC intra: 26.5% 36.0% 9.2% inter: 15.0% 18.5% 3.4%
  
  [libx264 @ 0000018c0d1321c0] i16 v,h,dc,p: 44% 39% 10%  7%
  
  [libx264 @ 0000018c0d1321c0] i8c dc,h,v,p: 36% 36% 21%  7%
  
  [libx264 @ 0000018c0d1321c0] kb/s:1383.65
  
  Exiting normally, received signal 2.

  So If you have some ideas for me it will help. Thank you