Stable Diffusion Animation

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  • ECCV2022-RIFE

    ECCV2022 - Real-Time Intermediate Flow Estimation for Video Frame Interpolation

  • Sure! This would be my approach (and tools) if I was smarter:

    If you make the generations with some similarities and use the right interpolation, you don't need 1000 images like my video and can obtain a smooth movement.

    First, generate images with some kind of visual anchor (background, an object). You can use frames generated using the previous frame as reference image, or the same seed but different prompt/parameters, or you can go wild using img2img/inpainting (btw I struggle to find an inpainting tool for Stable Diffusion: they seem to be just img2img with a mask, without contest).

    Then pass the generated images to one of the most recent interpolation algorithms, like this one https://github.com/megvii-research/ECCV2022-RIFE or the one used in the replicate we are commenting on (someone posted this reference: https://github.com/google-research/frame-interpolation )

    The first link reports some free and paid implementation and a Colab, so depending on how deep you want to go, you have a lot of choices.

    In the end, I'd use some good app to stabilize the image if needed, to get a more "calm" look. I use Luma Fusion, but it's a paid app (cheap, one-time payment, for iOS). I'm sure there are a ton of open-source implementations.

    It's an approach similar to the animation on replicate, but it allows a lot of fine-tuning and you can add new animation ideas/tools to the process.

    Nothing revolutionary, but I hope it helps!

    > You have generated some pretty cool designs.

    Thanks! I put in a lot of work in the last weeks. The project has a mission, I wrote something, but it's not ready yet. I believe it will be with the launch of Dall-E 8 :-/

  • frame-interpolation

    FILM: Frame Interpolation for Large Motion, In ECCV 2022.

  • Sure! This would be my approach (and tools) if I was smarter:

    If you make the generations with some similarities and use the right interpolation, you don't need 1000 images like my video and can obtain a smooth movement.

    First, generate images with some kind of visual anchor (background, an object). You can use frames generated using the previous frame as reference image, or the same seed but different prompt/parameters, or you can go wild using img2img/inpainting (btw I struggle to find an inpainting tool for Stable Diffusion: they seem to be just img2img with a mask, without contest).

    Then pass the generated images to one of the most recent interpolation algorithms, like this one https://github.com/megvii-research/ECCV2022-RIFE or the one used in the replicate we are commenting on (someone posted this reference: https://github.com/google-research/frame-interpolation )

    The first link reports some free and paid implementation and a Colab, so depending on how deep you want to go, you have a lot of choices.

    In the end, I'd use some good app to stabilize the image if needed, to get a more "calm" look. I use Luma Fusion, but it's a paid app (cheap, one-time payment, for iOS). I'm sure there are a ton of open-source implementations.

    It's an approach similar to the animation on replicate, but it allows a lot of fine-tuning and you can add new animation ideas/tools to the process.

    Nothing revolutionary, but I hope it helps!

    > You have generated some pretty cool designs.

    Thanks! I put in a lot of work in the last weeks. The project has a mission, I wrote something, but it's not ready yet. I believe it will be with the launch of Dall-E 8 :-/

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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