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  • 1
    Lightweight' GAN

    Lightweight' GAN

    Implementation of 'lightweight' GAN, proposed in ICLR 2021

    ...Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before they pass into a neural network (if you use augmentation). The general recommendation is to use suitable augs for your data and as many as possible, then after some time of training disable the most destructive (for image) augs. You can turn on automatic mixed precision with one flag --amp. You should expect it to be 33% faster and save up to 40% memory. ...
    Downloads: 0 This Week
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  • 2
    Dream Textures

    Dream Textures

    Stable Diffusion built-in to Blender

    ...Use the 'Seamless' option to create textures that tile perfectly with no visible seam. Texture entire scenes with 'Project Dream Texture' and depth to image. Re-style animations with the Cycles render pass. Run the models on your machine to iterate without slowdowns from a service. Create textures, concept art, and more with text prompts. Learn how to use the various configuration options to get exactly what you're looking for. Texture entire models and scenes with depth to image. Inpaint to fix up images and convert existing textures into seamless ones automatically. ...
    Downloads: 10 This Week
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  • 3
    Seadanse for Blender

    Seadanse for Blender

    Clay pass to Seedance 2.5 video, keeping the camera you keyframed

    A Blender extension and an Agent Skill that turn a grey clay pass into a Seedance 2.5 video. Home: https://seadanse.com/tool/blender-to-seedance-2-5 A text prompt cannot say where the camera starts, where it ends, or what blocks what. A blockout says all three. Render a Workbench clay pass from your scene camera, hand it over as the reference, and the take comes back following the path, framing and timing you keyframed.
    Downloads: 0 This Week
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  • 4
    Video Diffusion - Pytorch

    Video Diffusion - Pytorch

    Implementation of Video Diffusion Models

    ...Any new developments for text-to-video synthesis will be centralized at Imagen-pytorch. For conditioning on text, they derived text embeddings by first passing the tokenized text through BERT-large. You can also directly pass in the descriptions of the video as strings, if you plan on using BERT-base for text conditioning. This repository also contains a handy Trainer class for training on a folder of gifs. Each gif must be of the correct dimensions image_size and num_frames.
    Downloads: 1 This Week
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