ru-dalle
CodeFormer
ru-dalle | CodeFormer | |
---|---|---|
50 | 28 | |
1,639 | 13,556 | |
-0.3% | - | |
0.0 | 2.0 | |
over 1 year ago | about 1 month ago | |
Jupyter Notebook | Python | |
Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ru-dalle
- I trained a custom AI model for fakemon outputs. Feel free to use them for inspiration! No credit needed.
-
I trained an AI model to help me design fakebadge concepts. Full album in comments. Please feel free to take these for your own inspiration, too!
It’s a custom trained model, built in rudalle https://github.com/ai-forever/ru-dalle
-
Using AI to draft new ideas for legendaries.
It's a custom model, built from rudalle
-
SD photorealism to the extreme, is MJ really that better?
ru-dalle has had that feature for quite a while, as it was their first inpainting example notebook:
-
2 Google Colab notebooks are available for the large ruDALL-E Kandinsky model (12 billion parameters). The smaller ruDALL-E model has 1.3 billion parameters.
GitHub repo.
-
Colab notebook "pharmapsychotic modified rudalle" lets the user choose which of 4 ruDALL-E models to use
Colab notebook. There are actually 5 models, but I doubt the 12B parameter Kandinsky model is actually available per looking at this code.
-
Tree in a field.
This was made with a mini version of DALL-E: ruDALL-E
-
I trained an AI model to generate images of ancient Roman imperial denarii
Specifically, I fine-tuned ru-DALLE using a dataset consisting of ~1000 images of imperial denarii (ranging from Augustus through Maximinus Thrax) coupled with descriptions of each coin grabbed from OCRE. For example, the obverse description of this coin would be "Head of Augustus, bare, right" and the reverse description would be "Round shield, spear-head, and curved sword".
-
New ruDALL-E 1.3 billion parameter model version 3 has been released with ruDALL-E v1.0.0
One way to use the version 3 model is to use this official Colab notebook linked to in the ruDALL-E GitHub repo. I recommend making the changes mentioned in this post. If you want to use the older version 2 model with this Colab notebook, change 'Malevich' to 'Malevich_v2' in line "dalle = get_rudalle_model('Malevich', pretrained=True, fp16=True, device=device)" (relevant source code).
-
Preview of ruDALL-E v0.5.0 from the developer
# !pip install rudalle==0.0.1rc8 > /dev/null !pip3 install git+https://github.com/sberbank-ai/ru-dalle.git@feature/new_malevich
CodeFormer
-
Automatic1111 for Intel Arc (A380 Tested)
CodeFormer
-
Working with a prompt someone posted earlier ( workflow in comments)
https://github.com/sczhou/CodeFormer like this, did you install anything???
- Robust Blind Face Restoration with Codebook Lookup Transformer
-
Images created in Automatic1111 on M1 Mac - Blue tint
https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth to /stable-diffusion-webui/models/Codeformer/codeformer-v0.1.0.pth
-
How can I make this command run?
I just watched a youtube video of two minute papers and I was impressed by this face restauration ai.
- Towards Robust Blind Face Restoration with Codebook Lookup TransFormer | high quality faces!
-
I tried restoring this REALY old photo of my wife's great great great great Grandpa.
Have you tried this instead? https://github.com/sczhou/CodeFormer , you can try it at https://replicate.com/sczhou/codeformer
- 12 best AI websites to make your life easier [save 100s of hours]
-
Hoping to get this 1890's photo of my great grandmother and her 3 sisters restored as a Christmas present for my father.
CodeFormer is another good alternative to GFPGAN if you're not pleased with its results.
- new ai upscale tech
What are some alternatives?
NeuralTextToImage - Colabs for text prompt steered image generators
GFPGAN - GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
pytorch-seq2seq - Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
stable-diffusion-webui - Stable Diffusion web UI
fastai - The fastai deep learning library
GPEN
naver-webtoon-faces - Generative models on NAVER Webtoon faces
Real-ESRGAN-ncnn-vulkan - NCNN implementation of Real-ESRGAN. Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.
ganspace - Discovering Interpretable GAN Controls [NeurIPS 2020]
MidJourney-Styles-and-Keywords-Reference - A reference containing Styles and Keywords that you can use with MidJourney AI. There are also pages showing resolution comparison, image weights, and much more!
FinRL-Meta - FinRL-Meta: Dynamic datasets and market environments for FinRL.
stable-diffusion-ui - Easiest 1-click way to install and use Stable Diffusion on your computer. Provides a browser UI for generating images from text prompts and images. Just enter your text prompt, and see the generated image. [Moved to: https://github.com/easydiffusion/easydiffusion]