deepdream
pytorch-CycleGAN-and-pix2pix
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| deepdream | pytorch-CycleGAN-and-pix2pix | |
|---|---|---|
| 6 | 10 | |
| 13,211 | 21,998 | |
| - | - | |
| 0.0 | 2.8 | |
| over 1 year ago | 5 days ago | |
| Python | ||
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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deepdream
- Stable Audio: Fast Timing-Conditioned Latent Audio Diffusion
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List of AI-Models
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Kedu Ihe Bụ Simulacrum Subreddit?
Neural Style images are created with Tensorflow 2. Deep Dream images are created with Caffe. Wombo images are created with the Wombo Art app.
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I have no experience in coding, but is there an easy way for me to create generated monsters by randomly picking art components I've made and puting them together?
Maybe https://github.com/google/deepdream?
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I have read Neuromancer to an AI and this is how she imagines it!
Github
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Trippy Deepdream
That wasnt an app, its this: https://github.com/google/deepdream
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?
big-sleep - A simple command line tool for text to image generation, using OpenAI's CLIP and a BigGAN. Technique was originally created by https://twitter.com/advadnoun
pix2pixHD - Synthesizing and manipulating 2048x1024 images with conditional GANs
Caffe - Caffe: a fast open framework for deep learning.
generative-inpainting-pytorch - A PyTorch reimplementation for paper Generative Image Inpainting with Contextual Attention (https://arxiv.org/abs/1801.07892)
PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
pytorch-grad-cam - Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Keras - Deep Learning for humans
Deep-Fakes
mxnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
AnimeGAN - Generating Anime Images by Implementing Deep Convolutional Generative Adversarial Networks paper
markovify - A simple, extensible Markov chain generator.
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.