ramstorage / demofusion-colab

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🦒 Colab

Colab	Info
	DemoFusion_colab
	DemoFusion_img2img_colab (Thanks to radamar ❤)

🦆 Kaggle

Kaggle	Info
	DemoFusion_kaggle
	DemoFusion_img2img_kaggle

📋 Tutorial

2048x2048 will take around 800 seconds. (T4)

view_batch_size (int, defaults to 16): The batch size for multiple denoising paths. Typically, a larger batch size can result in higher efficiency but comes with increased GPU memory requirements.
stride (int, defaults to 64): The stride of moving local patches. A smaller stride is better for alleviating seam issues, but it also introduces additional computational overhead and inference time.
cosine_scale_1 (float, defaults to 3): Control the strength of skip-residual. For specific impacts, please refer to Appendix C in the DemoFusion paper.
cosine_scale_2 (float, defaults to 1): Control the strength of dilated sampling. For specific impacts, please refer to Appendix C in the DemoFusion paper.
cosine_scale_3 (float, defaults to 1): Control the strength of the Gaussian filter. For specific impacts, please refer to Appendix C in the DemoFusion paper.
sigma (float, defaults to 1): The standard value of the Gaussian filter. Larger sigma promotes the global guidance of dilated sampling, but has the potential of over-smoothing.
multi_decoder (bool, defaults to True): Determine whether to use a tiled decoder. Generally, when the resolution exceeds 3072x3072, a tiled decoder becomes necessary.
show_image (bool, defaults to False): Determine whether to show intermediate results during generation.

🧬 Code

https://github.com/PRIS-CV/DemoFusion

📄 Paper

https://arxiv.org/abs/2311.16973

🌐 Page

https://ruoyidu.github.io/demofusion/demofusion.html

🖼 Output

2023-12-07.08-44-13.mp4

guigjk.mp4

DemoFusion_img2img_colab

2023-12-08.12-43-35.mp4

2023-12-08.13-19-22.mp4

🏢 Sponsor

https://modelslab.com