SwinIR
Restormer
| SwinIR | Restormer | |
|---|---|---|
| 28 | 3 | |
| 4,091 | 1,545 | |
| - | - | |
| 0.0 | 3.8 | |
| about 1 month ago | 16 days ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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SwinIR
- A smooth and sharp image interpolation you probably haven't heard of
- Certain directories (e.g. SwinIR) are empty (version: Empire Media Science A1111 Web UI Installer)
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I used Real-ESRGAN to upscale my image, but if you zoom in you can see that “water particles” looks like some random lines and image overall looks cartoonish. Is there a way to fix it?
003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR-L_x4_GAN.pth
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Any luck changing the upscaler? They seem to be hard coded
I was trying to get a new upscaler working, as someone pointed me to one that did a good job of preserving and creating new details: https://github.com/JingyunLiang/SwinIR
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Spatial-temporal denoising
SwinIR: https://github.com/JingyunLiang/SwinIR
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A Monster Hunter: World Virtual Photography Tutorial - YouTube
Upscalers that I use SwinIR https://github.com/JingyunLiang/SwinIR https://github.com/AUTOMATIC1111/stable-diffusion-webui (Use 'extras' tab for the upscaler function) Topaz Gigapixel AI https://www.topazlabs.com/gigapixel-ai
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what are the alternatives to letsenhance.io?
You could try out chaiNNer, it is a free local/offline application. There are a lot of (upscaling) models which you can download an use with it. You can for example try out SwinIR-L (link will start a model download) or any other model you like depending on your input images.
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[R] Swin transformer while using a rectangular attention window
the relative attention bias can be made non-square in the original implementation, there is a parameter window_size, at 7, that is forced to (7,7) directly, but you can change it easily. https://github.com/JingyunLiang/SwinIR/blob/main/models/network_swinir.py
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Robot dance animation with Robo-Diffusion (1024x576)
Use SwinIR medium model to upscale by 2 times. This will result in a video of 2048x1152.
- Help Need to get my VQGAN images to 10000 x 10000
Restormer
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[R] Restormer: Efficient Transformer for High-Resolution Image Restoration (CVPR2022--ORAL) + Colab Demo + Gradio Web Demo
Code for https://arxiv.org/abs/2111.09881 found: https://github.com/swz30/Restormer
- Restormer: Efficient Transformer for High-Resolution Image Restoration
What are some alternatives?
Real-ESRGAN - Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
maxim-pytorch - [CVPR 2022 Oral] PyTorch re-implementation for "MAXIM: Multi-Axis MLP for Image Processing", with *training code*. Official Jax repo: https://github.com/google-research/maxim
image-super-resolution - 🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
NAFNet - The state-of-the-art image restoration model without nonlinear activation functions.
Real-ESRGAN-ncnn-vulkan - NCNN implementation of Real-ESRGAN. Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.
HRNet-Semantic-Segmentation - The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919
Ne2Ne-Image-Denoising - Deep Unsupervised Image Denoising, based on Neighbour2Neighbour training
transfiner - Mask Transfiner for High-Quality Instance Segmentation, CVPR 2022
chaiNNer - A node-based image processing GUI aimed at making chaining image processing tasks easy and customizable. Born as an AI upscaling application, chaiNNer has grown into an extremely flexible and powerful programmatic image processing application.
MPRNet - [CVPR 2021] Multi-Stage Progressive Image Restoration. SOTA results for Image deblurring, deraining, and denoising.
DirectVoxGO - Direct voxel grid optimization for fast radiance field reconstruction.