pytorch-CycleGAN-and-pix2pix
Real-ESRGAN
| pytorch-CycleGAN-and-pix2pix | Real-ESRGAN | |
|---|---|---|
| 10 | 131 | |
| 22,070 | 26,181 | |
| - | - | |
| 2.5 | 2.7 | |
| 1 day ago | 28 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
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pytorch-CycleGAN-and-pix2pix
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List of AI-Models
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- 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
Real-ESRGAN
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AI-Powered Nvidia RTX Video HDR Transforms Standard Video into HDR Video
It's not exactly what you're after, as it's anime specific and you need to process the video yourself (eg disassemble to frames, run the upscaler, then assemble back to a movie file), but Real-ESRGAN is really good:
https://github.com/xinntao/Real-ESRGAN/
It's pretty brilliant for cleaning up very old, low resolution anime.
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Photorealistic Video Generation with Diffusion Models
Just a note you can run upscaling on your home desktop with Real-ESRGAN:
https://github.com/xinntao/Real-ESRGAN
- What software to use for upscaling anime edits
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What neural net for SISR?
Maybe Real-ESRGAN is a good fit? Even tho it's a couple of years old
- Cant make concurrent calls to Model
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Outis my beloved
I'm glad you noticed! I upscaled the icon from the wiki using Real-ESRGAN's 4xplus anime model, then photoshopped out the text. Worked far better than waifu2x.
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ComicMerge (Beta testing version - SafeTensors)
A: Try using High-res Fix and R-ESRGAN 4x+ Anime6B as upscaler
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Is there any way to upscale local files permanently using Nvidia's RT VSR?
Maybe try this one https://github.com/xinntao/Real-ESRGAN it may work even better.
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YOASOBI Idol [3840 x 2160]
Screenshotted from the official music video, upscaled to 4k using a state of the art ML model.
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Compilation of (almost) all end of chapter panels
Do you happen to remember which chapter has that "scene"? You could also try to enhance it yourself, I did it using Real-ESRGAN, which is really easy to use.
What are some alternatives?
pix2pixHD - Synthesizing and manipulating 2048x1024 images with conditional GANs
ESRGAN - ECCV18 Workshops - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution. The training codes are in BasicSR.
generative-inpainting-pytorch - A PyTorch reimplementation for paper Generative Image Inpainting with Contextual Attention (https://arxiv.org/abs/1801.07892)
SwinIR - SwinIR: Image Restoration Using Swin Transformer (official repository)
pytorch-grad-cam - Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
GFPGAN - GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
Deep-Fakes
BSRGAN - Designing a Practical Degradation Model for Deep Blind Image Super-Resolution (ICCV, 2021) (PyTorch) - We released the training code!
AnimeGAN - Generating Anime Images by Implementing Deep Convolutional Generative Adversarial Networks paper
waifu2x - Image Super-Resolution for Anime-Style Art
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.
Real-ESRGAN-colab - A Real-ESRGAN model trained on a custom dataset