https://github.com/ai-forever/kandisuperres
Science Score: 36.0%
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○CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
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○DOI references
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✓Academic publication links
Links to: arxiv.org -
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○Scientific vocabulary similarity
Low similarity (9.7%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: ai-forever
- License: apache-2.0
- Language: Jupyter Notebook
- Default Branch: main
- Size: 182 MB
Statistics
- Stars: 24
- Watchers: 3
- Forks: 4
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
KandiSuperRes - diffusion model for super resolution
KandiSuperRes Flash Post | KandiSuperRes Post | 
| Telegram-bot | Our text-to-image model
KandiSuperRes Flash
Description
KandiSuperRes Flash is a new version of the diffusion model for super resolution. This model includes a distilled version of the KandiSuperRes model and a distilled model Kandinsky 3.0 Flash. KandiSuperRes Flash not only improves image clarity, but also corrects artifacts, draws details, improves image aesthetics. And one of the most important advantages is the ability to use the model in the "infinite super resolution" mode. For more information: details of architecture and training, example of generations check out our Habr post.
Installing
To install repo first one need to create conda environment:
conda create -n kandisuperres -y python=3.12;
source activate kandisuperres;
pip install -r requirements.txt;
How to use
Check our jupyter notebook KandiSuperRes.ipynb with example.
```python from KandiSuperRes import getSRpipeline from PIL import Image
srpipe = getSR_pipeline(device='cuda', fp16=True, flash=True, scale=2)
lrimage = Image.open('') srimage = srpipe(lrimage) ```
Infinite super resolution
With KandiSuperRes Flash you can infinitely enlarge images to x16 and more.
KandiSuperRes
Description
KandiSuperRes is an open-source diffusion model for x4 super resolution. This model is based on the Kandinsky 3.0 architecture with some modifications. For generation in 4K, the MultiDiffusion algorithm was used, which allows to generate panoramic images. For more information: details of architecture and training, example of generations check out our Habr post.
How to use
Check our jupyter notebook KandiSuperRes.ipynb with example.
```python from KandiSuperRes import getSRpipeline from PIL import Image
srpipe = getSR_pipeline(device='cuda', fp16=True, flash=False, scale=4)
lrimage = Image.open('') srimage = srpipe(lrimage) ```
Authors
Owner
- Name: AI Forever
- Login: ai-forever
- Kind: organization
- Location: Armenia
- Repositories: 60
- Profile: https://github.com/ai-forever
Creating ML for the future. AI projects you already know. We are non-profit organization with members from all over the world.
GitHub Events
Total
- Watch event: 10
Last Year
- Watch event: 10
Issues and Pull Requests
Last synced: about 1 year ago
All Time
- Total issues: 2
- Total pull requests: 2
- Average time to close issues: 2 days
- Average time to close pull requests: 9 minutes
- Total issue authors: 1
- Total pull request authors: 2
- Average comments per issue: 1.5
- Average comments per pull request: 0.0
- Merged pull requests: 2
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 1
- Average time to close issues: N/A
- Average time to close pull requests: 4 minutes
- Issue authors: 0
- Pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 0.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- aleksusklim (2)
Pull Request Authors
- anvilarth (2)
- NastyaMittseva (2)
Top Labels
Issue Labels
Pull Request Labels
Dependencies
- diffusers *
- einops *
- omegaconf *
- torch ==1.9.1
- torchaudio ==0.9.1
- torchvision ==0.10.1