🙋 About

GitHub recently published "Propelling your DevOps to new heights | GitHub InFocus", a exciting DevOPS related content :

Also, within the same period of time I watched an episode of "The Download" series (animated by @film_girl ):

The Download: Maintainer Month, .NET MAUI Goes GA, Flight Simulator: Top Gun, and more - YouTube

On this episode of The Download, Christina is on location at RenderATL, but is still here to offer the latest developer news, including:0:00 Intro0:59 Mainta...

youtube.com

This episode did introduce videogrep :

pip install videogrep

pip install vosk

Then came the idea :

What if I was analyzing "GitHub Infocus" with videogrep ?

This short post will guide through this first trial on videogrep and what I have been able to produce, discover... and the fun I also had.

☝️ Notice that I used the following excellent tutorial to perform this experience 👇

📥 Get the video with yt-dlp

First I want to get the YT video https://youtu.be/awQ7LFxfXWE
locally, therefore you can choose many encoding options and choose the one that best fits your needs (-F option) but in our case, we'll get the default one :

yt-dlp https://youtu.be/awQ7LFxfXWE -o propelling_your_devops.mp4 --write-auto-sub

Then you are ready for the next step : use videogrep.

📊 Text analysis with ngrams

videogrep makes it possible (and super easy) to analyze text within the (downloaded vtt files) subtitles.

So, what are the trendiest group of word ( called ngrams) in the video ? Let's find out !

While the single word analysis is not really interesting :

❯ videogrep --input propelling_your_devops.mp4.webm --ngrams 1 | head -10
to 449
and 352
that 347
you 323
the 322
we 306
a 255
of 251
so 167
is 157

2-ngrams are much more interesting about the underlying intents of the video :

❯ videogrep --input propelling_your_devops.mp4.webm --ngrams 2 | head -7
want to 97
that we 61
you can 55
you know 54
going to 51
we have 45
we can 45

... soon confirmed with the 3-grams :

❯ videogrep --input propelling_your_devops.mp4.webm --ngrams 3 | head -9
we want to 30
you want to 20
a lot of 19
want to make 19
make sure that 18
i'm going to 17
to make sure 17
we have a 16
i want to 13

🔬 Short analysis

With the help of ngrams, within less than a second we discover, by grepping the text of the video that

"GitHub focuses it attention on what they want... and also on what you want to achieve... and make"

👉 That first fact already tells us a lot.

☝️ It also puts in evidence

"the inclusive approach while using a lot of "I" and "We"

... which is also pretty exciting to onboard us on the product they are showcasing ❣️

✂️🎞️ Cut & get shorts

Now, the fun part.

You have made a text analysis but... wouldn't it be fun to see the movie of these grepped terms ?...

⚠️ Spoiler alert : Yes it is ❕ (and it's easy) 🤣

These are called fragments. Let's get some of them.

🎯 The "Want" movie

Let's get all the sentences containing "want"

videogrep --input propelling_your_devops.mp4.webm --search 'want' --resyncsubs 0.1 --output want_sentence.mp4

🤪 Also "we want" to get the "want" movie 🤣 :

videogrep --input propelling_your_devops.mp4.webm --search 'we want to' --search-type fragment --resyncsubs 0.1 --output want.mp4

🤓 GH talking about code

What we think the more when we think about Github services is : the "code".

Let's make them talk about "code"

videogrep --input propelling_your_devops.mp4.webm --search 'code' --search-type fragment --resyncsubs 0.1 --output code.mp4

➰ Github about GitHub 😹

Last but not least, I'd love to

see how GitHub talks about GitHub

videogrep --input propelling_your_devops.mp4.webm --search 'github' --search-type fragment --resyncsubs 0.1 --output github.mp4

🧑‍🎨 Conclusion

These tools open a very wide area for speech and video analysis... making it possible to put in evidence patterns, intentions or simply have fun.

Also, being aware that yt-dlp makes it possbible to download complete channel, playlists or search queries...

possibilities are endless.

🔖 Resources

• Vosk : speech recognition toolkit
• yt-dlp : A youtube-dl fork with additional features and fixes
• @sam_lavigne
• "GitHub Infocus 2022 analysis" playlist on YT

🗞️ News

In its 2.1.1 , videogrep adds some really cool features like (but not only) :

• Finding "non-english vtt subtitle files"
• "Examples that integrate with spaCy"