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I need to incorporate a small amount of 1080p HD shots in a 2160p 4K composition. I'm not impressed by default upscaling techniques like lanczos/bicubic/trilinear; it seems like my television does a better job of upscaling 1080p in real time. It may be time to learn some new tricks.

The FFmpeg manual mention a technique called Super Resolution, and it comes in two forms:

  • SRCNN: Super-Resolution Convolutional Neural Network model
  • ESPCN: Efficient Sub-Pixel Convolutional Neural Network model

Usually I can find many online sources for figuring out how to do something with FFmpeg. But I can't seem to find any tutorials on how to use this. I don't really understand it. I need to train (how?) a model (from what?), or get a pre-trained model (where?). I'd like to know how to get from 1080p to 2160p using this technique, assuming I know nothing about it.

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If all you need to do is superscale an image, going through the trouble of training neural networks is re-inventing the wheel. By all means, if you're studying computer science and are interested in AI/ML, I'd encourage you to look into it, but to just superscale an image, you don't need to train a neural network. There are tools available.

In DaVinci Resolve, for instance, all you need to do is right-click on a clip in the media pool, select "clip attributes...," then at the bottom of the "video" tab, change "Super Scale: None" to 2x, 3x, or 4x. I'm not sure if this feature is available in the free version, but I wouldn't be surprised if it is, because all they've done is integrated the open source ML bits of FFMPEG for you, trained the models for you, and bundled it as a feature. I'm sure Adobe has an equivalent feature, though I haven't used it.

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  • I don't mind using a pre-trained model, but I would like to know how to do this using ffmpeg exclusively so I can incorporate it in a pipeline (e.g. kdenlive). No commercial software. – Redsandro Jan 21 at 12:57

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