pytorch-CycleGAN-and-pix2pix
fast-stable-diffusion
| pytorch-CycleGAN-and-pix2pix | fast-stable-diffusion | |
|---|---|---|
| 10 | 239 | |
| 21,998 | 7,310 | |
| - | - | |
| 2.8 | 8.6 | |
| 8 days ago | 16 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | MIT License |
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pytorch-CycleGAN-and-pix2pix
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List of AI-Models
Click to Learn more...
- I want an A.I. to learn my art style so I can keep making art in my art style despite not having the time to do it.
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I'm looking for an AI Art generator from images
pix2pix (https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix) - This is a PyTorch implementation of the pix2pix algorithm for image-to-image translation. Given a set of images, the model can learn to generate a new image from a different domain that is similar to the input image.
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Seamless textures with SD and PBR maps with a pix2pix cGAN
Using junyanz/pytorch-CycleGAN-and-pix2pix as a basis for pix2pix, I applied the same blending method to fix seams. It essentially takes an input image and generates an output. The results depend on the paired training data. In this case, each map (height, roughness, etc.) is a separate checkpoint and had to be trained on paired training data with the diffuse as the input and the respective map as the output.
- IA art
- Segmentation and clasification with UNET
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Trying to understand PatchGAN discriminator
Code for https://arxiv.org/abs/1611.07004 found: https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix
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I made a 3d topographic map based on my recent civ6 game
pix2pix algorithm is used for translating Civ6Maps to heightmaps. Synthesized terrain was rendered in blender.
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This Wojak Does Not Exist
https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix
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Training a neural net to generate Wojaks
I'm working on creating a face-to-wojak model using PyTorch CycleGan/Pix2Pix [0] and found some of my outputs to be outrageous yet somehow relatable. People are into it so thought I'd share on HN
[0] https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix
fast-stable-diffusion
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Working Colab notebooks for training Dreambooth?
I tried using TheLastBen's fast dreambooth trainer. I managed to train a ckpt file but I can't run it.
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Running AUTOMATIC1111 on Google Colab
You have a colab from ThelastBen It uses to be thes best at the time when auto1111 was working in google colab free. https://github.com/TheLastBen/fast-stable-diffusion
- Stability AI releases its latest image-generating model, Stable Diffusion XL 1.0
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Google Colab disconnects after 5 mins of hosting A1111
Using https://github.com/TheLastBen/fast-stable-diffusion
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I'm kinda new to all of this and just wanted to ask... How can I fix something like this? Tried inpaint but didn't work even after changing parameters and img2img make it lose quality...
This repo offers a template how to start with SD on runpod https://github.com/TheLastBen/fast-stable-diffusion. But I know how to code, si I made my own solution.
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Unable to use ControlNet on AUTO1111 GUI - Google Colab Notebook
I can confirm I'm using the latest version of the colab notebook of this repo (https://github.com/TheLastBen/fast-stable-diffusion). Anyone can point to any solutions to this problem? Thanks in advance!
- Automatic 1111 not working
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Useful Links
TheLastBen's Fast DB SD Colabs, +25-50% speed increase, AUTOMATIC1111 + DreamBooth
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Can you use other base model to train your own model with TheLastBen or ShivamShrirao collab?
CalledProcessError Traceback (most recent call last) in () 182 wget.download('https://github.com/TheLastBen/fast-stable-diffusion/raw/main/Dreambooth/det.py') 183 print('Detecting model version...') --> 184 Custom_Model_Version=check_output('python det.py '+sftnsr+' --MODEL_PATH '+MODEL_PATH, shell=True).decode('utf-8').replace('\n', '') 185 clear_output() 186 print(''+Custom_Model_Version+' Detected')
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How to Install and Run Stable Diffusion in Automatic1111 with Deforum in Google Collab?
have you tried https://github.com/TheLastBen/fast-stable-diffusion ?
What are some alternatives?
pix2pixHD - Synthesizing and manipulating 2048x1024 images with conditional GANs
DeepFaceLab - DeepFaceLab is the leading software for creating deepfakes.
generative-inpainting-pytorch - A PyTorch reimplementation for paper Generative Image Inpainting with Contextual Attention (https://arxiv.org/abs/1801.07892)
InvokeAI - InvokeAI is a leading creative engine for Stable Diffusion models, empowering professionals, artists, and enthusiasts to generate and create visual media using the latest AI-driven technologies. The solution offers an industry leading WebUI, supports terminal use through a CLI, and serves as the foundation for multiple commercial products.
pytorch-grad-cam - Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
stable-diffusion-tensorflow - Stable Diffusion in TensorFlow / Keras
Deep-Fakes
efficient-dreambooth - [Moved to: https://github.com/smy20011/dreambooth-docker]
AnimeGAN - Generating Anime Images by Implementing Deep Convolutional Generative Adversarial Networks paper
stable-diffusion-webui-docker - Easy Docker setup for Stable Diffusion with user-friendly UI
PaddleGAN - PaddlePaddle GAN library, including lots of interesting applications like First-Order motion transfer, Wav2Lip, picture repair, image editing, photo2cartoon, image style transfer, GPEN, and so on.
stable-diffusion - A latent text-to-image diffusion model