PaddleGAN
pytorch-CycleGAN-and-pix2pix
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| PaddleGAN | pytorch-CycleGAN-and-pix2pix | |
|---|---|---|
| 2 | 10 | |
| 7,674 | 21,998 | |
| 1.1% | - | |
| 5.5 | 2.8 | |
| 18 days ago | 5 days ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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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.
PaddleGAN
- Make AI paint any photo - Paint Transformer: Feed Forward Neural Painting with Stroke Prediction by Songhua Liu et al. explained in 5 minutes
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Three Step to Get Multi-Personal "Mai-ha-hi"
By using PaddleGAN, ONLY use THREE STEPS to create a "Mai-ha-hi" video by using a photo containing more than one person.
pytorch-CycleGAN-and-pix2pix
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List of AI-Models
Click to Learn more...
- 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
What are some alternatives?
DeepFaceLab - DeepFaceLab is the leading software for creating deepfakes.
pix2pixHD - Synthesizing and manipulating 2048x1024 images with conditional GANs
AnimeGANv2 - [Open Source]. The improved version of AnimeGAN. Landscape photos/videos to anime
generative-inpainting-pytorch - A PyTorch reimplementation for paper Generative Image Inpainting with Contextual Attention (https://arxiv.org/abs/1801.07892)
Wav2Lip-GFPGAN - High quality Lip sync
pytorch-grad-cam - Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Image-Super-Resolution-via-Iterative-Refinement - Unofficial implementation of Image Super-Resolution via Iterative Refinement by Pytorch
Deep-Fakes
stylegan2-pytorch - Implementation of Analyzing and Improving the Image Quality of StyleGAN (StyleGAN 2) in PyTorch
AnimeGAN - Generating Anime Images by Implementing Deep Convolutional Generative Adversarial Networks paper
anycost-gan - [CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing
Anime-face-generation-DCGAN-webapp - A port of my Anime face generation using Pytorch into a Webapp