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• How to obtain time markers for video splitting using python/OpenCV

  10 novembre 2018, par Bleddyn Raw-Rees

  I’m working on my MSc project which is researching automated deletion of low value content in digital file stores. I’m specifically looking at the sort of long shots that often occur in natural history filming whereby a static camera is left rolling in order to capture the rare snow leopard or whatever. These shots may only have some 60s of useful content with perhaps several hours of worthless content either side.

  As a first step I have a simple motion detection program from Adrian Rosebrock’s tutorial [http://www.pyimagesearch.com/2015/05/25/basic-motion-detection-and-tracking-with-python-and-opencv/#comment-393376]. Next I intend to use FFMPEG to split the video.

  What I would like help with is how to get in and out points based on the first and last points that motion is detected in the video.

  Here is the code should you wish to see it...

  # import the necessary packages
  
  import argparse
  
  import datetime
  
  import imutils
  
  import time
  
  import cv2
  
  
  
  # construct the argument parser and parse the arguments
  
  ap = argparse.ArgumentParser()
  
  ap.add_argument("-v", "--video", help="path to the video file")
  
  ap.add_argument("-a", "--min-area", type=int, default=500, help="minimum area size")
  
  args = vars(ap.parse_args())
  
  
  
  # if the video argument is None, then we are reading from webcam
  
  if args.get("video", None) is None:
  
  camera = cv2.VideoCapture(0)
  
  time.sleep(0.25)
  
  
  
  # otherwise, we are reading from a video file
  
  else:
  
      camera = cv2.VideoCapture(args["video"])
  
  
  
  # initialize the first frame in the video stream
  
  firstFrame = None
  
  
  
  # loop over the frames of the video
  
  while True:
  
      # grab the current frame and initialize the occupied/unoccupied
  
      # text
  
      (grabbed, frame) = camera.read()
  
      text = "Unoccupied"
  
  
  
      # if the frame could not be grabbed, then we have reached the end
  
      # of the video
  
      if not grabbed:
  
          break
  
  
  
      # resize the frame, convert it to grayscale, and blur it
  
      frame = imutils.resize(frame, width=500)
  
      gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
  
      gray = cv2.GaussianBlur(gray, (21, 21), 0)
  
  
  
      # if the first frame is None, initialize it
  
      if firstFrame is None:
  
          firstFrame = gray
  
          continue
  
  
  
      # compute the absolute difference between the current frame and
  
      # first frame
  
      frameDelta = cv2.absdiff(firstFrame, gray)
  
      thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1]
  
  
  
      # dilate the thresholded image to fill in holes, then find contours
  
      # on thresholded image
  
      thresh = cv2.dilate(thresh, None, iterations=2)
  
      (_, cnts, _) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
  
  
  
      # loop over the contours
  
      for c in cnts:
  
          # if the contour is too small, ignore it
  
          if cv2.contourArea(c) < args["min_area"]:
  
              continue
  
  
  
          # compute the bounding box for the contour, draw it on the frame,
  
          # and update the text
  
          (x, y, w, h) = cv2.boundingRect(c)
  
          cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
  
          text = "Occupied"
  
  
  
      # draw the text and timestamp on the frame
  
      cv2.putText(frame, "Room Status: {}".format(text), (10, 20),
  
          cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
  
      cv2.putText(frame, datetime.datetime.now().strftime("%A %d %B %Y %I:%M:%S%p"),
  
          (10, frame.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1)
  
  
  
      # show the frame and record if the user presses a key
  
      cv2.imshow("Security Feed", frame)
  
      cv2.imshow("Thresh", thresh)
  
      cv2.imshow("Frame Delta", frameDelta)
  
      key = cv2.waitKey(1) & 0xFF
  
  
  
      # if the `q` key is pressed, break from the lop
  
      if key == ord("q"):
  
          break
  
  
  
  # cleanup the camera and close any open windows
  
  camera.release()
  
  cv2.destroyAllWindows()

• Unable to decode media issue on chrome browser

  20 octobre 2018, par Shrikant D

  I am experiencing an issue while playing media on my application. I am using html5 player which works fine on another browser but the media not worked on Google Chrome. Below is the ffmpeg output.

  ffmpeg version 3.4.1 Copyright (c) 2000-2017 the FFmpeg developers
  
  
  
    built with Apple LLVM version 8.0.0 (clang-800.0.42.1)
  
  
  
    configuration: --prefix=/usr/local/Cellar/ffmpeg/3.4.1 --enable-shared --enable-pthreads --enable-version3 --enable-hardcoded-tables --enable-avresample --cc=clang --host-cflags= --host-ldflags= --enable-gpl --enable-libmp3lame --enable-libx264 --enable-libxvid --enable-opencl --enable-videotoolbox --disable-lzma
  
  
  
    libavutil      55. 78.100 / 55. 78.100
  
  
  
    libavcodec     57.107.100 / 57.107.100
  
  
  
    libavformat    57. 83.100 / 57. 83.100
  
  
  
    libavdevice    57. 10.100 / 57. 10.100
  
  
  
    libavfilter     6.107.100 /  6.107.100
  
  
  
    libavresample   3.  7.  0 /  3.  7.  0
  
  
  
    libswscale      4.  8.100 /  4.  8.100
  
  
  
    libswresample   2.  9.100 /  2.  9.100
  
  
  
    libpostproc    54.  7.100 / 54.  7.100
  
  
  
  Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'sources-5a6b388fb093f.mp4':
  
  
  
    Metadata:
  
  
  
      major_brand     : mp42
  
  
  
      minor_version   : 0
  
  
  
      compatible_brands: mp42mp41
  
  
  
      creation_time   : 2017-10-31T01:45:10.000000Z
  
  
  
    Duration: 00:04:55.72, start: 0.000000, bitrate: 10300 kb/s
  
  
  
      Stream #0:0(eng): Video: h264 (Main) (avc1 / 0x31637661), yuv420p(tv, bt709), 1920x1080, 9975 kb/s, 59.94 fps, 59.94 tbr, 60k tbn, 119.88 tbc (default)
  
  
  
      Metadata:
  
  
  
        creation_time   : 2017-10-31T01:45:10.000000Z
  
  
  
        handler_name    : Alias Data Handler
  
  
  
        encoder         : AVC Coding
  
  
  
      Stream #0:1(eng): Audio: aac (LC) (mp4a / 0x6134706D), 48000 Hz, stereo, fltp, 317 kb/s (default)
  
  
  
      Metadata:
  
  
  
        creation_time   : 2017-10-31T01:45:10.000000Z
  
  
  
        handler_name    : Alias Data Handler

  The issue is replicable on Windows, Linux/Ubuntu and Mac on Google Chrome browser.

  UPDATED :

  render_id: 56
  
  player_id: 0
  
  origin_url: https://example.com/
  
  frame_url: https://example.com/node/83810
  
  frame_title: 
  
  url: https://example.com/sites/default/files/sources-5a6b388fb093f.mp4
  
  total_bytes: 380754023
  
  streaming: false
  
  single_origin: true
  
  passed_cors_access_check: false
  
  range_header_supported: true
  
  pipeline_state: kStopped
  
  info: Selected FFmpegVideoDecoder for video decoding, config: codec: h264 format: 1 profile: h264 main coded size: [1920,1080] visible rect: [0,0,1920,1080] natural size: [1920,1080] has extra data? true encryption scheme: Unencrypted rotation: 0°
  
  audio_channels_count: 2
  
  audio_codec_name: aac
  
  audio_sample_format: Float 32-bit planar
  
  audio_samples_per_second: 48000
  
  bitrate: 10300299
  
  found_audio_stream: true
  
  found_video_stream: true
  
  height: 1080
  
  max_duration: 295.722667
  
  start_time: 0
  
  time_base: 1/60000
  
  video_codec_name: h264
  
  video_format: PIXEL_FORMAT_I420
  
  video_is_encrypted: false
  
  width: 1920
  
  audio_dds: false
  
  audio_decoder: FFmpegAudioDecoder
  
  video_dds: false
  
  video_decoder: FFmpegVideoDecoder
  
  audio_buffering_state: BUFFERING_HAVE_ENOUGH
  
  video_buffering_state: BUFFERING_HAVE_ENOUGH
  
  for_suspended_start: false
  
  pipeline_buffering_state: BUFFERING_HAVE_ENOUGH
  
  duration: 295.722667
  
  event: PAUSE
  
  error: video decode error
  
  pipeline_error: PIPELINE_ERROR_DECODE

  Added chrome Player Properties for specific media.

• How to increase engagement and convert them into customers

  8 septembre 2020, par Joselyn Khor — Analytics Tips, Marketing

  Long gone are the days of simply tracking page views as a measure of engagement. Now it’s about engagement analysis, which is layered and provides insight for effective data-driven decisions.

  Discover how engaged people are with your website by uncovering behavioural patterns that tell you how well your site and content is or isn’t performing. This insight helps you re-evaluate, adapt and optimise your content and strategy. The more engaged they are, the more likely you’ll be able to guide them on a predetermined journey that results in more conversions ; and helps you reach the goals you’ve set for your business. 

  Why is visitor engagement important ?

  It’s vital to measure engagement if you have anything content related that plays a role in your customer’s journey. Some websites may find more value in figuring out how engaging their entire site is, while others may only want to zone in on, say, a blogging section, e-newsletters, social media channels or sign-up pages.

  In the larger scheme of things, engagement can be seen as what’s running your site. Every aspect of the buyer’s journey requires your visitors to be engaged. Whether you’re trying to attract, convert or build a loyal audience base, you need to know your content is optimised to maintain their attention and encourage them along the path to purchase, conversion or loyalty.

  How to increase engagement with Matomo

  You need to know what’s going right or wrong to eventually be able to deliver more riveting content your visitors can’t help but be drawn to. Learn how to apply Matomo’s easy-to-use features to increase engagement :

  1. The Behaviour feature
  2. Heatmaps
  3. A/B Testing
  4. Media Analytics
  5. Transitions
  6. Custom reports
  7. Other metrics to keep an eye on

  1. Look at the Behaviour feature

  It allows you to learn how visitors are responding to your content. This information is gathered by drawing insight from features such as site search, downloads, events and content interactions. Learn more

  

  Matomo’s top five ways to increase engagement with the Behaviour feature :

  Behaviour -> Pages
  Get complete insights on what pages your users engage with, what pages provide little value to your business and see the results of entry and exit pages. If important content is generating low traffic, you need to place it where it can be seen. Spend time where it matters and focus on the content that will engage with your users and see how it eventually converts them into customers.

  Behaviour -> Site search
  Site search tracks how people use your website’s internal search engine. You can see :

  • What search keywords visitors used on your website’s internal search.
  • Which of those keywords resulted in no results (what content your visitors are looking for but cannot find).
  • What pages visitors visited immediately after a search.
  • What search categories visitors use (if your website employs search categories).

  Behaviour -> Downloads
  What are users wanting to take away with them ? They could be downloading .pdfs, .zip files, ebooks, infographics or other free/paid resources. For example, if you were working for an education institution and created valuable information packs for students that you made available online in .pdf format. To see an increase in downloads meant students were finding the .pdfs and realising the need to download them. No downloads could mean the information packs weren’t being found which would be problematic.

  Behaviour -> Events
  Tracking events is a very useful way to measure the interactions your users have with your website content, which are not directly page views or downloads.

  How have Events been used effectively ? A great example comes from one of our customers, Catalyst. They wanted to capture and measure the user interaction of accordions (an area of content that expands or closes depending on how a user interacts with it) to see if people were actually getting all the information available to them on this one page. By creating an Event to record which accordion had been opened, as well as creating events for other user interactions, they were able to figure out which content got the most engagement and which got the least. Being able to see how visitors navigated through their website helped them optimise the site to ensure people were getting the relevant information they were craving.

  Behaviour -> Content interactions
  Content tracking allows you to track interaction within the content of your web page. Go beyond page views, bounce rates and average time spent on page with your content. Instead, you can analyse content interaction rates based on mouse clicking and configuring scrolling or hovering behaviours to see precisely how engaged your users are. If interaction rates are low, perhaps you need to restructure your page layout to grab your user’s attention sooner. Possibly you will get more interaction when you have more images or banner ads to other areas of your business.

  

  Watch this video to learn about the Behaviour feature

  2. Set up Heatmaps

  Effortlessly discover how your visitors truly engage with your most important web pages that impact the success of your business. Heatmaps shows you visually where your visitors try to click, move the mouse and how far down they scroll on each page.

  

  You don’t need to waste time digging for key metrics or worry about putting together tables of data to understand how your visitors are interacting with your website. Heatmaps make it easy and fast to discover where your users are paying their attention, where they have problems, where useless content is and how engaging your content is. Get insights that you cannot get from traditional reports. Learn more

  
  TRY IT FOR FREE
  

  3. Carry out A/B testing

  With A/B Testing you reduce risk in your decision-making and can test what your visitors are responding well to. 

  

  Ever had discussions with colleagues about where to place content on a landing page ? Or discussed what the call-to-action should be and assumed you were making the best decisions ? The truth is, you never know what really works the best (and what doesn’t) unless you test it. Learn more

  How to increase engagement with A/B Testing : Test, test and test. This is a surefire way to learn what content is leading your visitors on a path to conversion and what isn’t.

  4. Media Analytics

  Tells you how visitors are engaging with your video or audio content, and whether they’re leading to your desired conversions. Track :

  • How many plays your media gets and which parts they viewed
  • Finish rates
  • How your media was consumed over time
  • How media was consumed on specific days
  • Which locations your users were viewing your content from
  • Learn more

  

  How to increase engagement with Media Analytics : These metrics give a picture of how audiences are behaving when it comes to your content. By showing insights such as, how popular your media content is, how engaging it is and which days content will be most viewed, you can tailor content strategies to produce content people will actually find interesting and watch/listen.

  Matomo example : When we went through the feature video metrics on our own site to see how our videos were performing, we noticed our Acquisition video had a 95% completion rate. Even though it was longer than most videos, the stats showed us it had, by far, the most engagement. By using Media Analytics to get insights on the best and worst performing videos, we gathered useful info to help us better allocate resources effectively so that in the future, we’re producing more videos that will be watched.

  5. Investigate transitions

  See which page visitors are entering the site from and where they exit to. Transitions shows engagement on each page and whether the content is leading them to the pages you want them to be directed to.

  

  This gives you a greater understanding of user pathways. You may be assuming visitors are finding your content from one particular pathway, but figure out users are actually coming through other channels you never thought of. Through Transitions, you may discover and capitalise on new opportunities from external sites.

  How to increase engagement with Transitions : Identify clearly where users may be getting distracted to click away and where other pages are creating opportunity to click-through to conversion. 

  6. Create Custom Reports

  You can choose from over 200 dimensions and metrics to get the insights you need as well as various visualisation options. This makes understanding the data incredibly easy and you can get the insights you need instantly for faster results without the need for a developer. Learn more

  

  How to increase engagement with Custom Reports : Set custom reports to see when content is being viewed and figure out how engaged users are by looking at different hours of the day or which days of the week they’re visiting your website. For example, you could be wondering what hour of the day performed best for converting your customers. Understanding these metrics helps you figure out the best time to schedule your blog posts, pay-per-click advertising, edms or social media posts knowing that your visitors are more likely to convert at different times.

  
  TRY IT FOR FREE
  

  7. Other metrics to key an eye on …

  A good indication of a great experience and of engagement is whether your readers, viewers or listeners want to do it again and again.

  “Best” metrics are hard to determine so you’ll need to ask yourself what you want to do or what you want your site to do. How do you want your users to behave or what kind of buyer’s journey do you want them to have ?

  Want to know where to start ? Look at …

  • Bounce rate – a high bounce rate isn’t great as people aren’t finding what they’re looking for and are leaving without taking action. (This offers great opportunities as you can test to see why people are bouncing off your site and figure out what you need to change.)
  • Time on site – a long time on site is usually a good indication that people are spending time reading, navigating and being engaged with your website. 
  • Frequency of visit – how often do people come back to interact with the content on your website ? The higher the % of your visitors that come back time and time again will show how engaged they are with your content.
  • Session length/average session duration – how much time users spend on site each session
  • Pages per session – is great to show engagement because it shows visitors are happy going through your website and learn more about your business.

  Key takeaway

  Whichever stage of the buyer’s journey your visitors are in, you need to ensure your content is optimised for engagement so that visitors can easily spend time on your website.

  “Every single visit by every single visitor is no longer judged as a success or a failure at the end of 29 min (max) session in your analytics tool. Every visit is not a ‘last-visit’, rather it becomes a continuous experience leading to a win-win outcome.” – Avinash Kaushik

  As you can tell, one size does not fit all when it comes to analysing and measuring engagement, but with a toolkit of features, you can make sure you have everything you need to experiment and figure out the metrics that matter to the success of your business and website.

  Concurrently, these gentle nudges for visitors to consume more and more content encourages them along their path to purchase, conversion or loyalty. They get a more engaging website experience over time and you get happy visitors/customers who end up coming back for more.

  
  TRY IT FOR FREE
  

  Want to learn how to increase conversions with Matomo ? Look out for the final in this series : part 3 ! We’ll go through how you can boost conversions and meet your business goals with web analytics.