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• Homepage Design : Best Practices & Examples

  5 octobre 2022, par Erin

  Did you know users spend about 50 milliseconds deciding if they like your website’s homepage design or not ?

  With billions of websites and scrolling often done on the go, you have to make a strong first impression because the chances for a once-over are slim. 

  Learn how to design magnetically-appealing website homepages from this guide. 

  What is a homepage in web design ?

  Homepage is the front page of your website — a destination where users land when typing your website URL address. It’s located at the root of the website’s domain (e.g., matomo.org) or a subdomain (e.g., university.webflow.com).

  Design-wise a homepage has two goals :

  • Explain the purpose of the website and present overview information 
  • Provide top-level navigation to lower-level web pages (e.g., blog, sales pages, etc.) 

  Separately, a homepage is also the place where users will return each time they’ll feel stuck and want to start anew. Thus, your homepage website design should provide obvious navigation paths to other website areas.

  6 Must-Know Website Homepage Design Best Practices

  Behind every winning homepage design stands a detailed customer journey map. 

  A customer journey is a schematic representation of how site visitors will move around your website to accomplish various goals. 

  A good customer journey map lists different actions a user will take after landing on your website (e.g., browse product pages, save items to a wishlist, register an account, etc.) — and it does so for different audience segments. 

  

  Your homepage design should help users move from the first step on their journey (e.g., learning about your website) to the final one (e.g., converting to a paid customer). At the same time, your homepage should serve the needs of both new and returning visitors — prospects who may be at a different stage of their journey (e.g., consideration). 

  With the above in mind, let’s take a look at several website homepage design ideas and the reasons why they work. 

  1. Use Familiar Design Elements

  Whether you’re designing a new website or refreshing an old one, it’s always tempting to go “out of the box” — use horizontal scrolling, skip header navigation or include arty animations. 

  Bold design choices work for some brands, mainly those who aren’t using their website as a primary sales channel (e.g., luxury brands). 

  But unfamiliar design patterns can also intimidate a lot of shoppers. In one observational study, people were asked to guess where specific content (e.g., information on international calls) would be placed on a telecom website. 75% of users picked the same location. This means two things :

  • People already have expectations of where specific website information is typically placed 
  • Yet, one in four users struggles to identify the right areas even within standard website layouts

  So why make the job harder for them ? As UX consultant Peter Ramsey rightfully notes : 

  The truth is : designing the best experience isn’t about being unique, it’s about being easy. And guess what feels really easy to use ? Things that feel familiar.

  Therefore, analyse other homepage layout designs in your industry. Pay attention to the number and type of homepage screens and approaches to designing header/footer navigation. 

  Take some of those ideas as your “base”. Then make your homepage design on-brand with unique typography, icons, visuals and other graphic design elements.

  Take a cue from ICAM — a steel manufacturing company. Their niche isn’t typically exciting. Yet, their homepage design stops you in your tracks and tinkers your curiosity to discover more (even if you aren’t shopping for metalware). 

  

  The interesting part is that ICAM uses a rather standard homepage layout. You have a hero image in the first screen, followed by a multi-column layout of their industry expertise and an overview of manufacturers. 

  But this homepage design feels fresh because the company uses plenty of white space, bold typography and vibrant visuals. Also, they delay the creative twist (horizontal scrolling area) to the bottom of the homepage, meaning that it’s less likely to intimidate less confident web users. 

  2. Decide On The Optimal Homepage Layout 

  In web design, a homepage layout is your approach to visually organising different information on the screen. 

  Observant folks will notice that good homepage designs often have the same layout. For example, include a split-view “hero” screen with a call to action on the left and visuals (photo or video) on the left. 

  

  The reason for using similar layouts for website homepage design isn’t a lack of creativity. On the contrary, some layouts have become the “best practice” because they :

  • Offer a great user experience (UX) and don’t confuse first-time visitors 
  • Feel familiar and create a pleasurable sense of deja-vu among users 
  • Have proven to drive higher conversion rates through benchmarks and tests 

  Popular types of website homepage layouts : 

  • Single column – a classic option of presenting main content in a single, vertical column. Good choice for blogs, personal websites and simple corporate sites. 
  • Split screen layout divides the page in two equal areas with different information present. Works best for Ecommerce homepages (e.g., to separate different types of garments) or SaaS websites, offering two product types (e.g., a free personal product version and a business edition). 
  • Asymmetrical layout assumes dividing your homepage into areas of different size and styles. Asymmetry helps create specific focal points for users to draw their attention to the most prominent information. 
  • Grid of cards layout helps present a lot of information in a more digestible manner by breaking down bigger bulks of text into smaller cards — a graphic element, featuring an image and some texts. By tapping a card, users can then access extra content. 
  • Boxes are visually similar to cards, but can be of varying shape. For example, you can have a bigger header-width box area, followed by four smaller boxes within it. Both of these website layouts work well for Ecommerce. 
  • Featured image layout gives visuals (photos and videos) the most prominent placement on the homepage, with texts and other graphic design elements serving a secondary purpose. 
  • F-pattern layout is based on the standard eye movement most people have when reading content on the website. Eye tracking studies found that we usually pay the most attention to information atop of the page (header area), then scan horizontally before dripping down to the next vertical line until we find content that captures our attention. 

  User behaviour analytics (UBA) tools are the best way to determine what type of layout will work for your homepage. 

  For example, you can use Matomo Heatmaps and Session Recording to observe how users navigate your homepage, which areas or links they click and what blockers they face during navigation.

  

  Matomo can capture accurate behavioural insights because we track relative positions to elements within your websites. This approach allows us to provide accurate data for users with different browsers, operating systems, zoom-in levels and fonts. 

  The best part ? You can collect behavioural data from up to 100 different user segments to understand how different audience cohorts engage with your product.

  3. Include a One-Sentence Tagline

  A tagline is a one-line summary of what your company does and what its unique sales proposition (USP) is. It should be short, catchy and distinguish you from competitors.

  A modern homepage design practice is to include a call to action in the first screen. Why ? Because you then instantly communicate or remind of your value proposition to every user — and provide them with an easy way to convert whenever they are ready to do business with you. 

  Here’s how three companies with a similar product, a project management app, differentiate themselves through homepage taglines. 

  Monday.com positions itself as an operating system (OS) for work. 

  

  Basecamp emphasises its product simplicity and openly says that they are different from other overly-complex software. 

  

  Asana, in turn, addresses a familiar user pain point (siloed communication) that it attempts to fix with its product. 

  

  Coming up with the perfect homepage tagline is a big task. You may have plenty of ideas, but little confidence in what version will stick. 

  The best approach ? Let a series of A/B tests decide. You can test a roaster of homepage slogans on a rotating bi-weekly/monthly schedule and track how copy changes affect conversion rates. 

  With Matomo A/B test feature, you can create, track and manage all experiments straight from your web analytics app — and get consolidated reports on total page visitors and conversion rates per each tested variation. 

  

  Beyond slogans, you can also run A/B tests to validate submission form placements, button texts or the entire page layout. 

  For instance, you can benchmark how your new homepage design performs compared to the old version with a subset of users before making it publicly available. 

  4. Highlight The Main Tasks For The User

  Though casual browsing is a thing, most of us head to specific websites with a clear agenda — find information, compare prices, obtain services, etc. 

  Thus, your homepage should provide clear starting points for users’ main tasks (those you’ve also identified as conversion goals on your customer journey maps !).

  These tasks can include : 

  • Account registration 
  • Product demo request 
  • Newsletter sign-up 

  The best website homepage designs organically guide users through a set number of common tasks, one screen at a time. 

  Let’s analyse Sable homepage design. The company offers a no-fee bank account and a credit card product for soon-to-be US transplants. The main task a user has : Decide if they want to try Sable and hopefully open an account with them. 

  

  This mono-purpose page focuses on persuading a prospect that Sable is right for them. 

  The first screen hosts the main CTA with an animated drop-down arrow to keep scrolling. This is likely aimed at first-time visitors that just landed on the page from an online ad or social media post. 

  The second screen serves the main pitch — no-fee, no-hassle access to a US banking account that also helps you build your credit score. 

  The third screen encourages users to learn more about Sable Credit — the flagship product. For the sceptics, the fourth screen offers several more reasons to sign up for the credit product. 

  Then Sable moves on to pitching its second offering — a no-fee debit card with a cashback. Once again, the follow-up screen sweetens the deal by bringing up other perks (higher cashback for popular services like Amazon) and overcoming objections (no SSN required and multi-language support available). 

  The sequence ends with side-by-side product comparison and some extra social proof. 

  In Sable’s case, each homepage screen has a clear purpose and is designed to facilitate one specific user action — account opening. 

  For multi-product companies, the above strategy works great for designing individual landing pages. 

  5. Design Proper Navigation Paths

  All websites have two areas reserved for navigation : 

  • Header menu 
  • Footer menu 

  Designing an effective header menu is more important since it’s the primary tool visitors will use to discover other pages. 

  Your header menu can be :

  • Sticky — always visible as the person keeps scrolling. 
  • Static — e.g., a hidden drop-down menu. 

  If you go for a static header and have a longer homepage layout (e.g., 5+ screens), you also need to add extra navigation elements somewhere mid-page. Or else users might not figure out where to go next and merely bounce off. 

  You can do this by : 

  • Promoting other areas of your website (e.g., sub-category pages) by linking out to them 
  • Adding a carousel of “recent posts”, “recommended reads” and “latest products” 
  • Using buttons and CTAs to direct users towards specific actions (e.g., account registration) or assets (free eBook)

  For instance, cosmetics brand Typology doesn’t have a sticky header on the homepage. Instead, they prompt discovery by promoting different product categories (best sellers, bundles, latest arrivals) and their free skin diagnostic quiz — a great engagement mechanism to retain first time users.

  

  Once the user scrolls down to the bottom of the page, they should have an extra set of navigational options — aka footer links. 

  Again, these help steer the visitor towards discovering more content without scrolling back up to the top of your homepage. 

  Nielsen Norman Group says that people mostly use footers as :

  • A second chance to be convinced — after reading the entire homepage, the user is ready to give your product a go.
    
  • The last resort for hard-to-find content that’s not displayed in global header navigation (e.g., Terms and Conditions or shipping information pages).

  As a rule of thumb, you should designate the following information to the footer : 

  • Utility links (Contact page, Terms & Conditions, Privacy Policy, etc.) 
  • Secondary-task links (e.g., Career page, Investor Details, Media contacts, etc.) 
  • Brands within the organisation (if you operate several) 
  • Customer engagement link (email newsletters and social media buttons)

  The key is to keep the area compact — not more than one standard user screen resolution of 1280×720. 

  6. Show Users What’s Clickable (Or Not) 

  A homepage invites your site visitors on a journey. But if they don’t know which elements to click, they aren’t going to get anywhere.

  Good homepage design makes it obvious which page elements are clickable, i.e., can take the user to a new page or another segment of the homepage. 

  Here are several must-know homepage design tips for better on-page navigation : 

  • Use colour and underline or bold to highlight clickable words. Alternatively, you can change the browser cursor from a standard arrow into another element (e.g., a larger dot or a pointy finger) to indicate when the cursor hovers over a clickable website area. 
  • Make descriptive button texts that imply what will happen when a user clicks the page. Instead of using abstract and generic button texts like “see more” or “learn more”, try a more vibrant language like “dive in” for clicking through to a spa page. 
  • Use a unified hover area to show how different homepage design elements represent a single path or multiple navigation paths. When multiple items are encapsulated in one visual element (e.g., a box), users may be reluctant to click the image because they aren’t sure if it’s one large hit area leading to a single page or if there are multiple hit areas, leading to different pages. 

  Homepage of BEAUSiTE — a whimsical hotel in the Swiss Alps – embodies all of the above design principles. They change the cursor style whenever you scroll into a hit area, use emotive and creative micro-copy for all button texts and clearly distinguish between different homepage elements.

  

  How to Make Your Homepage Design Even More Impactful ? 

  Website homepage design is roughly 20% of pure design work and 80% of behind-the-scenes research. 

  To design a high-performing homepage you need to have data-backed answers to the following questions : 

  • Who are your primary and secondary target audiences ? 
  • Which tasks (1 to 4) you’d want to help them solve through your homepage ?

  You can get the answers to both questions from your web analytics data by using audience segmentation and page transition (behaviour flow) reports in Matomo. 

  Based on these, you can determine common user journeys and tasks people look to accomplish when visiting your website. Next, you can collect even more data with UBA tools  like heatmaps and user session recordings. Then translated the observed patterns into working homepage design ideas. 

  Improve your homepage design and conversion rates with Matomo. Start your free 21-day trial now ! 

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• Marketing Touchpoints : Examples, KPIs, and Best Practices

  11 mars 2024, par Erin

  The customer journey is rarely straightforward. Rather, each stage comprises numerous points of contact with your brand, known as marketing touchpoints. And each touchpoint is equally important to the customer experience. 

  This article will explore marketing touchpoints in detail, including how to analyse them with attribution models and which KPIs to track. It will also share tips on incorporating these touchpoints into your marketing strategy. 

  What are marketing touchpoints ? 

  Marketing touchpoints are the interactions that take place between brands and customers throughout the latter’s journey, either online or in person. 

  

  By understanding how customers interact with your brand before, during and after a purchase, you can identify the channels that contribute to starting, driving and closing buyer journeys. Not only that, but you’ll also learn how to optimise the customer experience. This can also help you : 

  • Promote customer loyalty through increased customer satisfaction
  • Improve your brand reputation and foster a more positive perception of your brand, supported by social proof 
  • Build brand awareness among prospective customers 
  • Reconnect with current customers to drive repeat business

  According to a 2023 survey, social media and video-sharing platforms are the leading digital touchpoints among US consumers.

  

  With the customer journey divided into three stages — awareness, consideration, and decision — we can group these interactions into three touchpoint segments, depending on whether they occur before, during or after a purchase. 

  Touchpoints before a purchase

  Touchpoints before a purchase are those initial interactions between potential customers and brands that occur during the awareness stage — before they’ve made a purchase decision. 

  Here are some key touchpoints at the pre-purchase stage : 

  • Customer reviews, forums, and testimonials 
  • Social media posts
  • Online ads 
  • Company events and product demos
  • Other digital touchpoints, like video content, blog posts, or infographics
  • Peer referral 

  In PwC’s 2024 Global Consumer Insights Pulse Survey, 54% of consumers listed search engines as their primary source of pre-purchase information, followed by Amazon (35%) and retailer websites (33%). 

  Here are the survey’s findings in Western Europe, specifically : 

  

  Social channels are another major pre-purchase touchpoint ; 25% of social media users aged 18 to 44 have made a purchase through a social media app over the past three months. 

  Touchpoints during a purchase

  Touchpoints during a purchase occur when the prospective customer has made their purchase decision. It’s the beginning of a (hopefully) lasting relationship with them. 

  It’s important to involve both marketing and sales teams here — and to keep track of conversion metrics. 

  Here are the main touchpoints at this stage : 

  • Company website pages 
  • Product pages and catalogues 
  • Communication between customers and sales reps 
  • Product packaging and labelling 
  • Point-of-sale (POS) — the final touchpoint the prospective customer will reach before making the final purchasing decision 

  Touchpoints after a purchase

  You can use touchpoints after a purchase to maintain a positive relationship and keep current customers engaged. Examples of touchpoints that contribute to a good post-purchase experience for the customer include the following : 

  • Thank-you emails 
  • Email newsletters 
  • Customer satisfaction surveys 
  • Cross-selling emails 
  • Renewal options 
  • Customer loyalty programs

  Email marketing remains significant across all touchpoint segments, with 44% of CMOs agreeing that it’s essential to their marketing strategy — and it also plays a particularly important role in the post-purchase experience. For 61.1% of marketing teams, email open rates are higher than 20%.

  

  Sixty-nine percent of consumers say they’ve stopped doing business with a brand following a bad experience, so the importance of customer service touchpoints shouldn’t be overlooked. Live chat, chatbots, self-service resources, and customer service teams are integral to the post-purchase experience.

  Attribution models : Assigning value to marketing touchpoints 

  Determining the most effective touchpoints — those that directly contribute to conversions — is a process known as marketing attribution. The goal here is to identify the specific channels and points of contact with prospective customers that result in revenue for the company.

  

  You can use these insights to understand — and maximise — marketing return on investment (ROI). Otherwise, you risk allocating your budget to the wrong channels. 

  It’s possible to group attribution models into two categories — single-touch and multi-touch — depending on whether you assign value to one or more contributing touchpoints.

  Single-touch attribution models, where you’re giving credit for the conversion to a single touchpoint, include the following :

  • First-touch attribution : This assigns credit for the conversion to the first interaction a customer had with a brand ; however, it fails to consider lower-funnel touchpoints.
  • Last-click attribution : This focuses only on bottom-of-funnel marketing and credits the last interaction the customer had with a brand before completing a purchase.
  • Last non-direct : Credits the touchpoint immediately preceding a direct touchpoint with all the credit.

  Multi-touch attribution models are more complex and distribute the credit for conversion across multiple relevant touchpoints throughout the customer journey :

  • Linear attribution : The simplest multi-touch attribution model assigns equal values to all contributing touchpoints.
  • Position-based or U-shaped attribution : This assigns the greatest value to the first and last touchpoint — with 40% of the conversion credit each — and then divides the remaining 20% across all the other touchpoints.
  • Time-decay attribution : This model assigns the most credit to the customer’s most recent interactions with a brand, assuming that the touchpoints that occur later in the journey have a bigger impact on the conversion.

  Consider the following when choosing the most appropriate attribution model for your business :

  • The length of your typical sales cycle
  • Your marketing goals : increasing awareness, lead generation, driving revenue, etc.
  • How many stages and touchpoints make up your sales funnel

  Sometimes, it even makes sense to measure marketing performance using more than one attribution model.

  With the sheer volume of data that’s constantly generated across numerous online touchpoints, from your website to social media channels, it’s practically impossible to collect and analyse it manually.

  You’ll need an advanced web analytics platform to identify key touchpoints and assign value to them.

  Matomo’s Marketing Attribution feature can accurately measure the performance of different touchpoints to ensure that you’re allocating resources to the right channels. This is done in a compliant manner, without the need of data sampling or requiring cookie consent screens (excluding in Germany and the UK), ensuring both accuracy and privacy compliance.

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  Customer journey KPIs for measuring marketing campaign performance 

  Measuring the impact of different touchpoints on marketing campaign performance can help you understand how customer interactions drive conversions — and how to optimise your future efforts. 

  

  Clearly, this is not a one-time effort. You should continuously reevaluate the crucial touchpoints that drive the most engagement at different stages of the customer journey. 

  Web analytics platforms can provide valuable insights into ever-changing consumer behaviours and trends and help you make informed decisions. 

  At the moment, Google is the most popular solution in the web analytics industry, with a combined market share of more than 70%. 

  However, if privacy, data accuracy, and GDPR compliance are a priority for you, Matomo is an alternative worth considering. 

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

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  KPIs to track before a purchase 

  During the pre-purchase stage, focus on the KPIs that measure the effectiveness of marketing activities across various online touchpoints — landing pages, email campaigns, social channels and ad placement on SERPs, for instance. 

  KPIs to track during the consideration stage include the following : 

  • Cost-per-click (CPC) : The CPC, the total cost of paid online advertising divided by the number of clicks those ads get, indicates whether you’re getting a good ROI. In the UK, the average CPC for search advertising is $1.22. Globally, it averages $0.62.
  • Engagement rate : The engagement rate, which is the total number of interactions divided by the number of followers, is useful for measuring the performance of social media touchpoints. Customer engagement also applies to other channels, like tracking average time on-page, form conversions, bounce rates, and other website interactions. 
  • Click-through rate (CTR) : The CTR — or the number of clicks your ads receive compared to the number of times they’re shown — helps you measure the performance of CTAs, email newsletters and pay-per-click (PPC) advertising.

  KPIs to track during a purchase 

  As a potential customer moves further down the sales funnel and reaches the decision stage, where they’re ready to make the choice to purchase, you should be tracking the following : 

  • Conversion rate : This is the percentage of leads that convert into customers by completing the desired action relative to the total number of website visitors. It shows you whether you’re targeting the right people and providing a frictionless checkout experience.
  • Sales revenue : This refers to the quantity of products sold multiplied by the product’s price. It helps you track the company’s ability to generate profit. 
  • Cost per conversion : This KPI is the total cost of online advertising in relation to the number of conversions. It measures the effectiveness of different marketing channels and the costs of converting prospective customers into buyers. It also forecasts future ad spend.

  KPIs to track after purchase 

  At the post-purchase stage, your priority should be gathering feedback : 

  Customer feedback surveys are great for collecting insights into customers’ post-purchase experience, opinions about your brand, products and services, and needs and expectations. 

  In addition to measuring customer satisfaction, these insights can help you identify points of friction, forecast future growth and revenue and spot customers at risk of churning. 

  Focus on the following customer satisfaction and retention metrics : 

  • Customer Satisfaction Score (CSAT) : This metric, which is gathered through customer satisfaction surveys, helps you gauge satisfaction levels. After all, 77% of consumers consider great customer service an important driver of brand loyalty.
  • Net Promoter Score (NPS) : Based on single-question customer surveys, NPS indicates how likely a customer is to recommend your business.
  • Customer Lifetime Value (CLV) : The CLV is the profit you can expect to generate from one customer throughout their relationship with your company. 
  • Customer Health Score (CHS) : This score can assess how “healthy” the customer’s relationship with your brand is and identify at-risk customers.

  Marketing touchpoints : Tips and best practices 

  Customer experience is more important today than ever. 

  

  Salesforce’s 2022 State of the Connected Consumer report indicated that, for 88% of customers, the experience the brand provides is just as important as the product itself. 

  Here’s how you can build your customer touchpoint strategy and use effective touchpoints to improve customer satisfaction, build a loyal customer base, deliver better digital experiences and drive growth : 

  Understand the customer’s end-to-end experience 

  The typical customer’s journey follows a non-linear path of individual experiences that shape their awareness and brand preference. 

  Seventy-three percent of customers expect brands to understand their needs. So, personalising each interaction and delivering targeted content at different touchpoint segments — supported by customer segmentation and tools like Matomo — should be a priority. 

  Try to put yourself in the prospective customer’s shoes and understand their motivation and needs, focusing on their end-to-end experience rather than individual interactions. 

  Create a customer journey map 

  Once you understand how prospective customers interact with your brand, it becomes easier to map their journey from the pre-purchase stage to the actual purchase and beyond. 

  By creating these visual “roadmaps,” you make sure that you’re delivering the right content on the right channels at the right times and to the right audience — the key to successful marketing.

  Identify best-performing digital touchpoints 

  You can use insights from marketing attribution to pinpoint areas that are performing well. 

  By analysing the data provided by Matomo’s Marketing Attribution feature, you can determine which digital touchpoints are driving the most conversions or engagement, allowing you to focus your resources on optimising these channels for even greater success. 

  This targeted approach helps maximise the effectiveness of your marketing efforts and ensures a higher return on investment.

  Try Matomo for Free

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

  Start for free

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  Discover key marketing touchpoints with Matomo 

  The customer’s journey rarely follows a direct route. If you hope to reach more customers and improve their experience, you’ll need to identify and manage individual marketing touchpoints every step of the way.

  While this process looks different for every business, it’s important to remember that your customers’ experience begins long before they interact with your brand for the first time — and carries on long after they complete the purchase. 

  In order to find these touchpoints and measure their effectiveness across multiple marketing channels, you’ll have to rely on accurate data — and a powerful web analytics tool like Matomo can provide those valuable marketing insights. 

  Try Matomo free for 21-days. No credit card required.

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• FFMPEG not working from Python subprocess.Popen but works from command line

  21 novembre 2017, par Stuart Clarke

  I’m trying to run a FFMPEG script from within python 3.5.2. the FFMPEG command runs fine from the command line but fails within the python script.

  The function I use to execute the FFMPEG command is

  def ffmpeg(args):
  
      err = None
  
      command = [
  
          ffmpegcmd, '-y',
  
          '-loglevel', loglevel
  
      ] + args
  
      print("\n\n\n")
  
      print(command)
  
      print("\n\n\n")
  
      print(" ".join(command))
  
      ffmpeg = subprocess.Popen(command, stderr=subprocess.PIPE ,stdout=subprocess.PIPE, universal_newlines=True)
  
      while err == None:
  
          out, err = ffmpeg.communicate()
  
          time.sleep(1)
  
      if err and loglevel=='fatal':
  
          print(" ".join(command))
  
          raise Exception(err)
  
      print(err)

  The value for args is :

  ['-i', '/var/www/temp/film.mp4', '-vf', 'scale=1920:1080:force_original_aspect_ratio=decrease,pad=1920:1080:x=(1920-iw)/2:y=(1080-ih)/2:color=black', '/var/www/temp/videoHD.mp4']

  such that the resultant command being passed to subprocess.Popen is :

  ['ffmpeg', '-y', '-loglevel', 'verbose', '-i', '/var/www/temp/film.mp4', '-vf', 'scale=1920:1080:force_original_aspect_ratio=decrease,pad=1920:1080:x=(1920-iw)/2:y=(1080-ih)/2:color=black', '/var/www/temp/videoHD.mp4']

  The value of loglevel is verbose only for troubleshooting but is intended to run as fatal. There are also some print commands only in place for troubleshooting.

  The reason for wanting to increase the resolution is so that it can be combined later with higher resolution videos.

  The result when running from within python is :

  ffmpeg version 3.3.4-2~16.04.york0 Copyright (c) 2000-2017 the FFmpeg developers
  
    built with gcc 5.4.0 (Ubuntu 5.4.0-6ubuntu1~16.04.4) 20160609
  
    configuration: --prefix=/usr --extra-version='2~16.04.york0' --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --enable-gpl --disable-stripping --enable-avresample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libmp3lame --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-omx --enable-openal --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libopencv --enable-libx264 --enable-shared
  
    libavutil      55. 58.100 / 55. 58.100
  
    libavcodec     57. 89.100 / 57. 89.100
  
    libavformat    57. 71.100 / 57. 71.100
  
    libavdevice    57.  6.100 / 57.  6.100
  
    libavfilter     6. 82.100 /  6. 82.100
  
    libavresample   3.  5.  0 /  3.  5.  0
  
    libswscale      4.  6.100 /  4.  6.100
  
    libswresample   2.  7.100 /  2.  7.100
  
    libpostproc    54.  5.100 / 54.  5.100
  
  [h264 @ 0x7f741a37a560] Reinit context to 640x368, pix_fmt: yuv420p
  
  Input #0, mov,mp4,m4a,3gp,3g2,mj2, from '/var/www/temp/film.mp4':
  
    Metadata:
  
      major_brand     : isom
  
      minor_version   : 512
  
      compatible_brands: isomiso2avc1mp41
  
      encoder         : Lavf57.71.100
  
    Duration: 00:06:19.80, start: 0.000000, bitrate: 451 kb/s
  
      Stream #0:0(und): Video: h264 (High), 1 reference frame (avc1 / 0x31637661), yuv420p(left), 640x358 (640x368), 313 kb/s, 30 fps, 30 tbr, 15360 tbn, 60 tbc (default)
  
      Metadata:
  
        handler_name    : VideoHandler
  
      Stream #0:1(und): Audio: aac (LC) (mp4a / 0x6134706D), 48000 Hz, stereo, fltp, 128 kb/s (default)
  
      Metadata:
  
        handler_name    : SoundHandler
  
  Stream mapping:
  
    Stream #0:0 -> #0:0 (h264 (native) -> h264 (libx264))
  
    Stream #0:1 -> #0:1 (aac (native) -> aac (native))
  
  Press [q] to stop, [?] for help
  
  [h264 @ 0x7f741a3bc700] Reinit context to 640x368, pix_fmt: yuv420p
  
  [graph_1_in_0_1 @ 0x7f741a5315e0] tb:1/48000 samplefmt:fltp samplerate:48000 chlayout:0x3
  
  [Parsed_scale_0 @ 0x7f741a54e000] w:1920 h:1080 flags:'bicubic' interl:0
  
  [graph 0 input from stream 0:0 @ 0x7f741a54f6a0] w:640 h:358 pixfmt:yuv420p tb:1/15360 fr:30/1 sar:0/1 sws_param:flags=2
  
  [Parsed_scale_0 @ 0x7f741a54e000] w:640 h:358 fmt:yuv420p sar:0/1 -> w:1920 h:1074 fmt:yuv420p sar:0/1 flags:0x4
  
  [Parsed_pad_1 @ 0x7f741a54eac0] w:1920 h:1074 -> w:1920 h:1080 x:0 y:2 color:0x000000FF
  
  [libx264 @ 0x7f741a5509e0] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 AVX2 LZCNT BMI2
  
  [libx264 @ 0x7f741a5509e0] profile High, level 4.0
  
  [libx264 @ 0x7f741a5509e0] 264 - core 148 r2795 aaa9aa8 - H.264/MPEG-4 AVC codec - Copyleft 2003-2017 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=6 lookahead_threads=1 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=25 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00
  
  Output #0, mp4, to '/var/www/temp/videoHD.mp4':
  
    Metadata:
  
      major_brand     : isom
  
      minor_version   : 512
  
      compatible_brands: isomiso2avc1mp41
  
      encoder         : Lavf57.71.100
  
      Stream #0:0(und): Video: h264 (libx264), 1 reference frame ([33][0][0][0] / 0x0021), yuv420p(left), 1920x1080, q=-1--1, 30 fps, 15360 tbn, 30 tbc (default)
  
      Metadata:
  
        handler_name    : VideoHandler
  
        encoder         : Lavc57.89.100 libx264
  
      Side data:
  
        cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: -1
  
      Stream #0:1(und): Audio: aac (LC) ([64][0][0][0] / 0x0040), 48000 Hz, stereo, fltp, delay 1024, 128 kb/s (default)
  
      Metadata:
  
        handler_name    : SoundHandler
  
        encoder         : Lavc57.89.100 aac

  This results in a file with no content.

  When I run the command from the command line I need to add single quotes around the -vf video filters scale=1920:1080:force_original_aspect_ratio=decrease,pad=1920:1080:x=(1920-iw)/2:y=(1080-ih)/2:color=black so the whole command becomes :

  ffmpeg -y -loglevel verbose -i /var/www/temp/film.mp4 -vf 'scale=1920:1080:force_original_aspect_ratio=decrease,pad=1920:1080:x=(1920-iw)/2:y=(1080-ih)/2:color=black' /var/www/temp/videoHD.mp4

  Running this command gives the required result.

  ffmpeg version 3.3.4-2~16.04.york0 Copyright (c) 2000-2017 the FFmpeg developers
  
    built with gcc 5.4.0 (Ubuntu 5.4.0-6ubuntu1~16.04.4) 20160609
  
    configuration: --prefix=/usr --extra-version='2~16.04.york0' --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --enable-gpl --disable-stripping --enable-avresample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libmp3lame --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-omx --enable-openal --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libopencv --enable-libx264 --enable-shared
  
    libavutil      55. 58.100 / 55. 58.100
  
    libavcodec     57. 89.100 / 57. 89.100
  
    libavformat    57. 71.100 / 57. 71.100
  
    libavdevice    57.  6.100 / 57.  6.100
  
    libavfilter     6. 82.100 /  6. 82.100
  
    libavresample   3.  5.  0 /  3.  5.  0
  
    libswscale      4.  6.100 /  4.  6.100
  
    libswresample   2.  7.100 /  2.  7.100
  
    libpostproc    54.  5.100 / 54.  5.100
  
  [h264 @ 0x7f3a55c17560] Reinit context to 640x368, pix_fmt: yuv420p
  
  Input #0, mov,mp4,m4a,3gp,3g2,mj2, from '/var/www/temp/film.mp4':
  
    Metadata:
  
      major_brand     : isom
  
      minor_version   : 512
  
      compatible_brands: isomiso2avc1mp41
  
      encoder         : Lavf57.71.100
  
    Duration: 00:06:19.80, start: 0.000000, bitrate: 451 kb/s
  
      Stream #0:0(und): Video: h264 (High), 1 reference frame (avc1 / 0x31637661), yuv420p(left), 640x358 (640x368), 313 kb/s, 30 fps, 30 tbr, 15360 tbn, 60 tbc (default)
  
      Metadata:
  
        handler_name    : VideoHandler
  
      Stream #0:1(und): Audio: aac (LC) (mp4a / 0x6134706D), 48000 Hz, stereo, fltp, 128 kb/s (default)
  
      Metadata:
  
        handler_name    : SoundHandler
  
  Stream mapping:
  
    Stream #0:0 -> #0:0 (h264 (native) -> h264 (libx264))
  
    Stream #0:1 -> #0:1 (aac (native) -> aac (native))
  
  Press [q] to stop, [?] for help
  
  [h264 @ 0x7f3a55c59700] Reinit context to 640x368, pix_fmt: yuv420p
  
  [graph_1_in_0_1 @ 0x7f3a55dce5e0] tb:1/48000 samplefmt:fltp samplerate:48000 chlayout:0x3
  
  [Parsed_scale_0 @ 0x7f3a55deb000] w:1920 h:1080 flags:'bicubic' interl:0
  
  [graph 0 input from stream 0:0 @ 0x7f3a55dec6a0] w:640 h:358 pixfmt:yuv420p tb:1/15360 fr:30/1 sar:0/1 sws_param:flags=2
  
  [Parsed_scale_0 @ 0x7f3a55deb000] w:640 h:358 fmt:yuv420p sar:0/1 -> w:1920 h:1074 fmt:yuv420p sar:0/1 flags:0x4
  
  [Parsed_pad_1 @ 0x7f3a55debac0] w:1920 h:1074 -> w:1920 h:1080 x:0 y:2 color:0x000000FF
  
  [libx264 @ 0x7f3a55ded9e0] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 AVX2 LZCNT BMI2
  
  [libx264 @ 0x7f3a55ded9e0] profile High, level 4.0
  
  [libx264 @ 0x7f3a55ded9e0] 264 - core 148 r2795 aaa9aa8 - H.264/MPEG-4 AVC codec - Copyleft 2003-2017 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=6 lookahead_threads=1 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=25 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00
  
  Output #0, mp4, to '/var/www/temp/videoHD.mp4':
  
    Metadata:
  
      major_brand     : isom
  
      minor_version   : 512
  
      compatible_brands: isomiso2avc1mp41
  
      encoder         : Lavf57.71.100
  
      Stream #0:0(und): Video: h264 (libx264), 1 reference frame ([33][0][0][0] / 0x0021), yuv420p(left), 1920x1080, q=-1--1, 30 fps, 15360 tbn, 30 tbc (default)
  
      Metadata:
  
        handler_name    : VideoHandler
  
        encoder         : Lavc57.89.100 libx264
  
      Side data:
  
        cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: -1
  
      Stream #0:1(und): Audio: aac (LC) ([64][0][0][0] / 0x0040), 48000 Hz, stereo, fltp, delay 1024, 128 kb/s (default)
  
      Metadata:
  
        handler_name    : SoundHandler
  
        encoder         : Lavc57.89.100 aac
  
  frame=   46 fps=0.0 q=0.0 size=       0kB time=00:00:01.62 bitrate=   0.0kbits/s
  
  frame=   59 fps= 47 q=29.0 size=     116kB time=00:00:02.04 bitrate= 464.8kbits/
  
  frame=   74 fps= 41 q=29.0 size=     223kB time=00:00:02.56 bitrate= 714.8kbits/
  
  frame=   87 fps= 35 q=29.0 size=     344kB time=00:00:02.98 bitrate= 942.4kbits/
  
  frame=   98 fps= 33 q=29.0 size=     427kB time=00:00:03.34 bitrate=1043.4kbits/
  
      blah
  
      blah
  
      blah
  
  frame=11347 fps= 21 q=29.0 size=   97550kB time=00:06:18.32 bitrate=2112.3kbits/
  
  frame=11363 fps= 21 q=29.0 size=   97713kB time=00:06:18.85 bitrate=2112.8kbits/
  
  frame=11380 fps= 21 q=29.0 size=   97795kB time=00:06:19.41 bitrate=2111.5kbits/
  
  No more output streams to write to, finishing.
  
  frame=11392 fps= 21 q=-1.0 Lsize=   98519kB time=00:06:19.77 bitrate=2125.1kbits/s speed=0.69x    
  
  video:92124kB audio:5986kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.416313%
  
  Input file #0 (/var/www/temp/film.mp4):
  
    Input stream #0:0 (video): 11392 packets read (14892948 bytes); 11392 frames decoded; 
  
    Input stream #0:1 (audio): 17803 packets read (6112540 bytes); 17802 frames decoded (18229248 samples); 
  
    Total: 29195 packets (21005488 bytes) demuxed
  
  Output file #0 (/var/www/temp/videoHD.mp4):
  
    Output stream #0:0 (video): 11392 frames encoded; 11392 packets muxed (94334785 bytes); 
  
    Output stream #0:1 (audio): 17802 frames encoded (18229248 samples); 17803 packets muxed (6129981 bytes); 
  
    Total: 29195 packets (100464766 bytes) muxed
  
  [libx264 @ 0x7f3a55ded9e0] frame I:74    Avg QP:19.08  size: 51540
  
  [libx264 @ 0x7f3a55ded9e0] frame P:3506  Avg QP:21.34  size: 19348
  
  [libx264 @ 0x7f3a55ded9e0] frame B:7812  Avg QP:24.07  size:  2904
  
  [libx264 @ 0x7f3a55ded9e0] consecutive B-frames:  1.3% 20.2%  4.6% 73.9%
  
  [libx264 @ 0x7f3a55ded9e0] mb I  I16..4: 19.7% 73.6%  6.7%
  
  [libx264 @ 0x7f3a55ded9e0] mb P  I16..4:  3.2%  6.4%  0.1%  P16..4: 52.5%  7.6%  2.6%  0.0%  0.0%    skip:27.6%
  
  [libx264 @ 0x7f3a55ded9e0] mb B  I16..4:  0.2%  0.2%  0.0%  B16..8: 23.2%  0.4%  0.0%  direct: 0.5%  skip:75.5%  L0:51.8% L1:46.6% BI: 1.6%
  
  [libx264 @ 0x7f3a55ded9e0] 8x8 transform intra:66.4% inter:94.0%
  
  [libx264 @ 0x7f3a55ded9e0] coded y,uvDC,uvAC intra: 33.6% 53.4% 7.3% inter: 5.3% 14.2% 0.0%
  
  [libx264 @ 0x7f3a55ded9e0] i16 v,h,dc,p: 22% 27%  5% 46%
  
  [libx264 @ 0x7f3a55ded9e0] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 29% 19% 20%  4%  7%  7%  7%  5%  4%
  
  [libx264 @ 0x7f3a55ded9e0] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 31% 28% 11%  3%  9%  7%  6%  3%  2%
  
  [libx264 @ 0x7f3a55ded9e0] i8c dc,h,v,p: 49% 21% 20% 10%
  
  [libx264 @ 0x7f3a55ded9e0] Weighted P-Frames: Y:0.5% UV:0.1%
  
  [libx264 @ 0x7f3a55ded9e0] ref P L0: 63.4%  8.9% 21.4%  6.3%  0.0%
  
  [libx264 @ 0x7f3a55ded9e0] ref B L0: 89.3%  9.1%  1.6%
  
  [libx264 @ 0x7f3a55ded9e0] ref B L1: 98.1%  1.9%
  
  [libx264 @ 0x7f3a55ded9e0] kb/s:1987.38
  
  [aac @ 0x7f3a55deee80] Qavg: 1160.814

  and the resulting video is fine.

  Any ideas ?

  Cheers,

  Stu

  Edit

  It was suggested that I use a new function to do much the same thing. So I added the following function and used it for the command that I’m having trouble with :

  def ffmpegPro(args):
  
      err = None
  
      for i, arg in enumerate(args):
  
          if(" " in arg or "(" in arg or "[" in arg):
  
              args[i] = "\"" + arg + "\""
  
      command = [
  
          ffmpegcmd, '-y',
  
          '-loglevel', loglevel
  
      ] + args
  
      commandStr = " ".join(command)
  
      print("\n\n\n")
  
      print(command)
  
      print("\n\n\n")
  
      print(commandStr)
  
      ffmpeg = subprocess.Popen(commandStr, stderr=subprocess.PIPE, stdout=subprocess.PIPE, universal_newlines=True, shell=True)
  
      while err == None:
  
          out, err = ffmpeg.communicate()
  
          time.sleep(1)
  
      if ffmpeg.returncode == 0 and all([os.path.exists(f) for f in (videoStorage['data_small'], videoStorage['data_big'])]):
  
          print("Job done.")
  
      else:
  
          print("ERROR")
  
          print(err)

  The resulting command can now be used in python or at the command line without needing to be changed at all. The command is :

  ffmpeg -y -loglevel verbose -i /var/www/temp/film.mp4 -vf "scale=1920:1080:force_original_aspect_ratio=decrease,pad=1920:1080:x=(1920-iw)/2:y=(1080-ih)/2:color=black" /var/www/temp/videoHD.mp4

  The result when executed in python is

  ffmpeg version 3.3.4-2~16.04.york0 Copyright (c) 2000-2017 the FFmpeg developers
  
    built with gcc 5.4.0 (Ubuntu 5.4.0-6ubuntu1~16.04.4) 20160609
  
    configuration: --prefix=/usr --extra-version='2~16.04.york0' --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --enable-gpl --disable-stripping --enable-avresample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libmp3lame --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-omx --enable-openal --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libopencv --enable-libx264 --enable-shared
  
    libavutil      55. 58.100 / 55. 58.100
  
    libavcodec     57. 89.100 / 57. 89.100
  
    libavformat    57. 71.100 / 57. 71.100
  
    libavdevice    57.  6.100 / 57.  6.100
  
    libavfilter     6. 82.100 /  6. 82.100
  
    libavresample   3.  5.  0 /  3.  5.  0
  
    libswscale      4.  6.100 /  4.  6.100
  
    libswresample   2.  7.100 /  2.  7.100
  
    libpostproc    54.  5.100 / 54.  5.100
  
  [h264 @ 0x7fb75053d560] Reinit context to 640x368, pix_fmt: yuv420p
  
  Input #0, mov,mp4,m4a,3gp,3g2,mj2, from '/var/www/temp/film.mp4':
  
    Metadata:
  
      major_brand     : isom
  
      minor_version   : 512
  
      compatible_brands: isomiso2avc1mp41
  
      encoder         : Lavf57.71.100
  
    Duration: 00:06:19.80, start: 0.000000, bitrate: 451 kb/s
  
      Stream #0:0(und): Video: h264 (High), 1 reference frame (avc1 / 0x31637661), yuv420p(left), 640x358 (640x368), 313 kb/s, 30 fps, 30 tbr, 15360 tbn, 60 tbc (default)
  
      Metadata:
  
        handler_name    : VideoHandler
  
      Stream #0:1(und): Audio: aac (LC) (mp4a / 0x6134706D), 48000 Hz, stereo, fltp, 128 kb/s (default)
  
      Metadata:
  
        handler_name    : SoundHandler
  
  Stream mapping:
  
    Stream #0:0 -> #0:0 (h264 (native) -> h264 (libx264))
  
    Stream #0:1 -> #0:1 (aac (native) -> aac (native))
  
  Press [q] to stop, [?] for help
  
  [h264 @ 0x7fb75057f700] Reinit context to 640x368, pix_fmt: yuv420p
  
  [graph_1_in_0_1 @ 0x7fb7506f45e0] tb:1/48000 samplefmt:fltp samplerate:48000 chlayout:0x3
  
  [Parsed_scale_0 @ 0x7fb750711000] w:1920 h:1080 flags:'bicubic' interl:0
  
  [graph 0 input from stream 0:0 @ 0x7fb7507126a0] w:640 h:358 pixfmt:yuv420p tb:1/15360 fr:30/1 sar:0/1 sws_param:flags=2
  
  [Parsed_scale_0 @ 0x7fb750711000] w:640 h:358 fmt:yuv420p sar:0/1 -> w:1920 h:1074 fmt:yuv420p sar:0/1 flags:0x4
  
  [Parsed_pad_1 @ 0x7fb750711ac0] w:1920 h:1074 -> w:1920 h:1080 x:0 y:2 color:0x000000FF
  
  [libx264 @ 0x7fb7507139e0] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 AVX2 LZCNT BMI2
  
  [libx264 @ 0x7fb7507139e0] profile High, level 4.0
  
  [libx264 @ 0x7fb7507139e0] 264 - core 148 r2795 aaa9aa8 - H.264/MPEG-4 AVC codec - Copyleft 2003-2017 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=6 lookahead_threads=1 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=25 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00
  
  Output #0, mp4, to '/var/www/temp/videoHD.mp4':
  
    Metadata:
  
      major_brand     : isom
  
      minor_version   : 512
  
      compatible_brands: isomiso2avc1mp41
  
      encoder         : Lavf57.71.100
  
      Stream #0:0(und): Video: h264 (libx264), 1 reference frame ([33][0][0][0] / 0x0021), yuv420p(left), 1920x1080, q=-1--1, 30 fps, 15360 tbn, 30 tbc (default)
  
      Metadata:
  
        handler_name    : VideoHandler
  
        encoder         : Lavc57.89.100 libx264
  
      Side data:
  
        cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: -1
  
      Stream #0:1(und): Audio: aac (LC) ([64][0][0][0] / 0x0040), 48000 Hz, stereo, fltp, delay 1024, 128 kb/s (default)
  
      Metadata:
  
        handler_name    : SoundHandler
  
        encoder         : Lavc57.89.100 aac
  
  Killed

  Note the Killed at the end. Is this significant and why is it only happening when executed in the script ?

  Here is the output from the command line which results in a successful video file.

  ffmpeg version 3.3.4-2~16.04.york0 Copyright (c) 2000-2017 the FFmpeg developers
  
    built with gcc 5.4.0 (Ubuntu 5.4.0-6ubuntu1~16.04.4) 20160609
  
    configuration: --prefix=/usr --extra-version='2~16.04.york0' --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --enable-gpl --disable-stripping --enable-avresample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libmp3lame --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-omx --enable-openal --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libopencv --enable-libx264 --enable-shared
  
    libavutil      55. 58.100 / 55. 58.100
  
    libavcodec     57. 89.100 / 57. 89.100
  
    libavformat    57. 71.100 / 57. 71.100
  
    libavdevice    57.  6.100 / 57.  6.100
  
    libavfilter     6. 82.100 /  6. 82.100
  
    libavresample   3.  5.  0 /  3.  5.  0
  
    libswscale      4.  6.100 /  4.  6.100
  
    libswresample   2.  7.100 /  2.  7.100
  
    libpostproc    54.  5.100 / 54.  5.100
  
  [h264 @ 0x7fb52cfb3560] Reinit context to 640x368, pix_fmt: yuv420p
  
  Input #0, mov,mp4,m4a,3gp,3g2,mj2, from '/var/www/temp/film.mp4':
  
    Metadata:
  
      major_brand     : isom
  
      minor_version   : 512
  
      compatible_brands: isomiso2avc1mp41
  
      encoder         : Lavf57.71.100
  
    Duration: 00:06:19.80, start: 0.000000, bitrate: 451 kb/s
  
      Stream #0:0(und): Video: h264 (High), 1 reference frame (avc1 / 0x31637661), yuv420p(left), 640x358 (640x368), 313 kb/s, 30 fps, 30 tbr, 15360 tbn, 60 tbc (default)
  
      Metadata:
  
        handler_name    : VideoHandler
  
      Stream #0:1(und): Audio: aac (LC) (mp4a / 0x6134706D), 48000 Hz, stereo, fltp, 128 kb/s (default)
  
      Metadata:
  
        handler_name    : SoundHandler
  
  Stream mapping:
  
    Stream #0:0 -> #0:0 (h264 (native) -> h264 (libx264))
  
    Stream #0:1 -> #0:1 (aac (native) -> aac (native))
  
  Press [q] to stop, [?] for help
  
  [h264 @ 0x7fb52cff5700] Reinit context to 640x368, pix_fmt: yuv420p
  
  [graph_1_in_0_1 @ 0x7fb52d16a5e0] tb:1/48000 samplefmt:fltp samplerate:48000 chlayout:0x3
  
  [Parsed_scale_0 @ 0x7fb52d187000] w:1920 h:1080 flags:'bicubic' interl:0
  
  [graph 0 input from stream 0:0 @ 0x7fb52d1886a0] w:640 h:358 pixfmt:yuv420p tb:1/15360 fr:30/1 sar:0/1 sws_param:flags=2
  
  [Parsed_scale_0 @ 0x7fb52d187000] w:640 h:358 fmt:yuv420p sar:0/1 -> w:1920 h:1074 fmt:yuv420p sar:0/1 flags:0x4
  
  [Parsed_pad_1 @ 0x7fb52d187ac0] w:1920 h:1074 -> w:1920 h:1080 x:0 y:2 color:0x000000FF
  
  [libx264 @ 0x7fb52d1899e0] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 AVX2 LZCNT BMI2
  
  [libx264 @ 0x7fb52d1899e0] profile High, level 4.0
  
  [libx264 @ 0x7fb52d1899e0] 264 - core 148 r2795 aaa9aa8 - H.264/MPEG-4 AVC codec - Copyleft 2003-2017 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=6 lookahead_threads=1 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=25 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00
  
  Output #0, mp4, to '/var/www/temp/videoHD.mp4':
  
    Metadata:
  
      major_brand     : isom
  
      minor_version   : 512
  
      compatible_brands: isomiso2avc1mp41
  
      encoder         : Lavf57.71.100
  
      Stream #0:0(und): Video: h264 (libx264), 1 reference frame ([33][0][0][0] / 0x0021), yuv420p(left), 1920x1080, q=-1--1, 30 fps, 15360 tbn, 30 tbc (default)
  
      Metadata:
  
        handler_name    : VideoHandler
  
        encoder         : Lavc57.89.100 libx264
  
      Side data:
  
        cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: -1
  
      Stream #0:1(und): Audio: aac (LC) ([64][0][0][0] / 0x0040), 48000 Hz, stereo, fltp, delay 1024, 128 kb/s (default)
  
      Metadata:
  
        handler_name    : SoundHandler
  
        encoder         : Lavc57.89.100 aac
  
  frame=   47 fps=0.0 q=0.0 size=       0kB time=00:00:01.66 bitrate=   0.0kbits/s
  
  frame=   59 fps= 41 q=29.0 size=     116kB time=00:00:02.04 bitrate= 464.8kbits/
  
  frame=   71 fps= 35 q=29.0 size=     201kB time=00:00:02.45 bitrate= 671.3kbits/
  
  frame=   80 fps= 31 q=29.0 size=     276kB time=00:00:02.75 bitrate= 822.0kbits/
  
      Blah
  
      Blah
  
      Blah
  
  frame=11337 fps= 21 q=29.0 size=   97503kB time=00:06:17.98 bitrate=2113.2kbits/
  
  frame=11351 fps= 21 q=26.0 size=   97572kB time=00:06:18.45 bitrate=2112.1kbits/
  
  frame=11371 fps= 21 q=29.0 size=   97745kB time=00:06:19.11 bitrate=2112.1kbits/
  
  frame=11390 fps= 21 q=29.0 size=   97852kB time=00:06:19.73 bitrate=2111.0kbits/
  
  No more output streams to write to, finishing.
  
  frame=11392 fps= 21 q=-1.0 Lsize=   98519kB time=00:06:19.77 bitrate=2125.1kbits/s speed=0.688x    
  
  video:92124kB audio:5986kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.416313%
  
  Input file #0 (/var/www/temp/film.mp4):
  
    Input stream #0:0 (video): 11392 packets read (14892948 bytes); 11392 frames decoded; 
  
    Input stream #0:1 (audio): 17803 packets read (6112540 bytes); 17802 frames decoded (18229248 samples); 
  
    Total: 29195 packets (21005488 bytes) demuxed
  
  Output file #0 (/var/www/temp/videoHD.mp4):
  
    Output stream #0:0 (video): 11392 frames encoded; 11392 packets muxed (94334785 bytes); 
  
    Output stream #0:1 (audio): 17802 frames encoded (18229248 samples); 17803 packets muxed (6129981 bytes); 
  
    Total: 29195 packets (100464766 bytes) muxed
  
  [libx264 @ 0x7fb52d1899e0] frame I:74    Avg QP:19.08  size: 51540
  
  [libx264 @ 0x7fb52d1899e0] frame P:3506  Avg QP:21.34  size: 19348
  
  [libx264 @ 0x7fb52d1899e0] frame B:7812  Avg QP:24.07  size:  2904
  
  [libx264 @ 0x7fb52d1899e0] consecutive B-frames:  1.3% 20.2%  4.6% 73.9%
  
  [libx264 @ 0x7fb52d1899e0] mb I  I16..4: 19.7% 73.6%  6.7%
  
  [libx264 @ 0x7fb52d1899e0] mb P  I16..4:  3.2%  6.4%  0.1%  P16..4: 52.5%  7.6%  2.6%  0.0%  0.0%    skip:27.6%
  
  [libx264 @ 0x7fb52d1899e0] mb B  I16..4:  0.2%  0.2%  0.0%  B16..8: 23.2%  0.4%  0.0%  direct: 0.5%  skip:75.5%  L0:51.8% L1:46.6% BI: 1.6%
  
  [libx264 @ 0x7fb52d1899e0] 8x8 transform intra:66.4% inter:94.0%
  
  [libx264 @ 0x7fb52d1899e0] coded y,uvDC,uvAC intra: 33.6% 53.4% 7.3% inter: 5.3% 14.2% 0.0%
  
  [libx264 @ 0x7fb52d1899e0] i16 v,h,dc,p: 22% 27%  5% 46%
  
  [libx264 @ 0x7fb52d1899e0] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 29% 19% 20%  4%  7%  7%  7%  5%  4%
  
  [libx264 @ 0x7fb52d1899e0] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 31% 28% 11%  3%  9%  7%  6%  3%  2%
  
  [libx264 @ 0x7fb52d1899e0] i8c dc,h,v,p: 49% 21% 20% 10%
  
  [libx264 @ 0x7fb52d1899e0] Weighted P-Frames: Y:0.5% UV:0.1%
  
  [libx264 @ 0x7fb52d1899e0] ref P L0: 63.4%  8.9% 21.4%  6.3%  0.0%
  
  [libx264 @ 0x7fb52d1899e0] ref B L0: 89.3%  9.1%  1.6%
  
  [libx264 @ 0x7fb52d1899e0] ref B L1: 98.1%  1.9%
  
  [libx264 @ 0x7fb52d1899e0] kb/s:1987.38
  
  [aac @ 0x7fb52d18ae80] Qavg: 1160.814

  Any more ideas why this is being handled differently in python as opposed to the command line ?

  I’m believe this is a version issue and that is why the below answer did not work for me, things were fine before I upgraded but since then a lot of things have been playing up. I upgraded both ffmpeg and python versions and don’t really want to go back if it can be avoided.

  Thanks,

  Stu