PTI
encoder4editing
| PTI | encoder4editing | |
|---|---|---|
| 4 | 2 | |
| 881 | 915 | |
| - | - | |
| 2.7 | 0.0 | |
| 6 months ago | 10 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | MIT License |
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PTI
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NEW just released AI DragGAN is MIND-BLOWING! Revolutionary way to edit images.
you can do it by yourself with specific tool https://github.com/danielroich/PTI. Autor of repository even made Google Colab notebook.
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So Draggan code is finally released
from Dragan readme: This GUI supports editing GAN-generated images. To edit a real image, you need to first perform GAN inversion using tools like PTI. Then load the new latent code and model weights to the GUI.
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[D] New SOTA StyleGAN2 inversion paper explained in 5 minutes: Pivotal Tuning for Latent-based Editing of Real Images (PTI) by Daniel Roich et al.
[Full Explanation Post] [Arxiv] [Code]
- [R] Finally, Actual Real images editing using StyleGAN
encoder4editing
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[R] a Metric for finding the best StyleGAN Latent Encoders
Right now we have encoders like pSp and restyle or encoder4editing, but how can we tell which one performs better than the other?
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Edit a human face image with text-to-image using Google Colab notebook StyleCLIP by orpatashnik. 3 transformations shown. Details in a comment.
If you want to edit an existing image, the GitHub page says to use encoder4editing, but it currently has no code. If that is remedied, then set experiment_type=edit and latent_path to the output file generated by encoder4editing. If you use experiment_type=edit and latent_path=None, a random StyleGAN image is used.
What are some alternatives?
stylegan-encoder - StyleGAN Encoder - converts real images to latent space
StyleCLIP - Official Implementation for "StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery" (ICCV 2021 Oral)
ganspace - Discovering Interpretable GAN Controls [NeurIPS 2020]
pixel2style2pixel - Official Implementation for "Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation" (CVPR 2021) presenting the pixel2style2pixel (pSp) framework
DragGAN - Official Code for DragGAN (SIGGRAPH 2023)
DualStyleGAN - [CVPR 2022] Pastiche Master: Exemplar-Based High-Resolution Portrait Style Transfer
restyle-encoder - Official Implementation for "ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinement" (ICCV 2021) https://arxiv.org/abs/2104.02699
Deep-Learning - In-depth tutorials on deep learning. The first one is about image colorization using GANs (Generative Adversarial Nets).
FixNoise - Official Pytorch Implementation for "Fix the Noise: Disentangling Source Feature for Controllable Domain Translation" (CVPR 2023, CVPRW 2022 Best paper)
sd-webui-dragGAN-extension - extension of stable diffusion webui for dragGAN
GAN-Anime-Characters - Applied several Generative Adversarial Networks (GAN) techniques such as: DCGAN, WGAN and StyleGAN to generate Anime Faces and Handwritten Digits.