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Description

In that project I try to build model, which can define cuts in video.

Data Sources

I've downloaded videos from Youtube and cut them by Kdenlive.

file clip name youtube link
0 videos/0.mp4 Rammstein - Du Hast https://www.youtube.com/watch?v=W3q8Od5qJio
1 videos/1.mp4 Rammstein - Rosenrot https://www.youtube.com/watch?v=af59U2BRRAU
2 videos/2.mp4 Rammstein - Sonne https://www.youtube.com/watch?v=StZcUAPRRac
3 videos/3.mp4 Замай - Одинокое Пламя https://www.youtube.com/watch?v=jn9pwdmKpXU
4 videos/4.mp4 SKRILLEX - Bangarang feat. Sirah https://www.youtube.com/watch?v=YJVmu6yttiw
5 videos/5.mp4 IC3PEAK - Плак-Плак https://www.youtube.com/watch?v=Y6tDdjOmsCY
6 videos/6.mp4 Crystal Castles - Celestica https://www.youtube.com/watch?v=IsxNUl1IHnE
7 videos/7.mp4 Grimes - Oblivion https://www.youtube.com/watch?v=JtH68PJIQLE
8 videos/8.mp4 Lana Del Rey - Born To Die https://www.youtube.com/watch?v=Bag1gUxuU0g
9 videos/9.mp4 Rihanna - Diamonds https://www.youtube.com/watch?v=lWA2pjMjpBs
10 videos/10.mp4 Joji - Gimme Love https://www.youtube.com/watch?v=jPan651rVMs

There are disolve and dip to white/black transitions in source videos. I don't label the first as cut, but for the second that's possible to see where exactly shot changes, so I labeled them as cuts almost accurate.

The example of cut with dip to black transition you can see in pics/dipToBlack_cuts0.png.

How I managed this data

There are 3 Rammstein clips, which contain a lot of actions, like fires, explosions, flashs or just jerks. I used 2 of them to learn and validate. Then checked the model with the 3rd. And I got many false positive results.

So I checked how the model predict cuts on less agressive video, and tool the video of an another artist. And yes, the model predicts cuts of more peacefull videos a little better.

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