data-efficient-gans
stable-diffusion-docker
data-efficient-gans | stable-diffusion-docker | |
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9 | 4 | |
1,258 | 710 | |
0.2% | - | |
0.0 | 6.7 | |
6 months ago | 4 months ago | |
Python | Python | |
BSD 2-clause "Simplified" License | GNU Affero General Public License v3.0 |
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data-efficient-gans
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[D] Has anyone tried GAN "tricks" on VAEs?
Code for https://arxiv.org/abs/2006.10738 found: https://github.com/mit-han-lab/data-efficient-gans
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What StyleGan model to use for a custom dataset of small size?
I would like to make a tiny project with GANs using some high quality pictures of a single individual. I am planning to get around 500 of these and then x-flip them, however I am not sure what model I should consider for the training. I have used StyleGan2 ADA for another project which ended quite well, but I had around 14k pictures, here now the training size is much smaller and I was therefore thinking about using DiffAugment which has seemingly promising results with just 100 images.
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This Bot Crime Did Not Occur
I used a modified version of this repo, and there's also the official NVIDIA implementation, though neither have official notebooks. You can Google 'StyleGAN2 ADA Colab' and find a few starting points that way, but wait a few hours and I can clean up my notebook and post it here!
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[P] Differentiable augmentation for GANs - Implementation and explanation
Paper: https://arxiv.org/abs/2006.10738
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Deepspeed x Stylegan?
There are some repos which I've looked at to add deepspeed to such as DiffAugment-stylegan2-pytorch, lucidrains/stylegan2-pytorch and eps696/stylegan2 (which is in tensorflow so it would need to be translated to pytorch as deepspeed only works with pytorch right now).
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Model takes seconds to train per epoch with 1 accuracy
Here is the paper using GANs with few data points https://arxiv.org/abs/2006.10738
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Looking for resources regarding GANs trained on my own stuff.
Hey, for image gans, you can use smooth data aumentation https://github.com/mit-han-lab/data-efficient-gans in case you have a reasonable sized dataset.
stable-diffusion-docker
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Do you guys recommend any GPU cloud hosting services for stable diffusion?
Honestly though, you’re being a bit paranoid about it. Running your own local install would be much easier, and if you use .safetensors then from my understanding you’re pretty safe. You could also run it using the Docker container for a bit more security, though imo it’s not worth the headache.
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Stable Diffusion CLI apps?
You could try a dockerized implementation of it like this one https://github.com/fboulnois/stable-diffusion-docker
- Keep yourself safe when downloading models, Pickle malware scanner GUI for Stable Diffusion
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Do we have a ready to go LXC container with web UI for stable diffusion yet ?
https://github.com/pieroit/stable-diffusion-jupyterlab-docker/ https://github.com/fboulnois/stable-diffusion-docker
What are some alternatives?
stylegan2-ada-pytorch - StyleGAN2-ADA - Official PyTorch implementation
stable-diffusion-webui-docker - Easy Docker setup for Stable Diffusion with user-friendly UI
Fast-SRGAN - A Fast Deep Learning Model to Upsample Low Resolution Videos to High Resolution at 30fps
ComfyUI-to-Python-Extension - A powerful tool that translates ComfyUI workflows into executable Python code.
SDEdit - PyTorch implementation for SDEdit: Image Synthesis and Editing with Stochastic Differential Equations
stable-diffusion-pytorch - Yet another PyTorch implementation of Stable Diffusion (probably easy to read)
gansformer - Generative Adversarial Transformers
Sketch-Guided-Stable-Diffusion - Unofficial Implementation of the Google Paper - https://sketch-guided-diffusion.github.io/
generative_inpainting - DeepFill v1/v2 with Contextual Attention and Gated Convolution, CVPR 2018, and ICCV 2019 Oral
sdxl-demos - Python demos for testing out the Stable Diffusion's XL (SDXL 0.9) model.
cartoonize - A demo webapp to convert images and videos into cartoon!
stable-diffusion-webui - Stable Diffusion web UI