t81_558_deep_learning
T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis (by jeffheaton)
image-super-resolution
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks. (by idealo)
| t81_558_deep_learning | image-super-resolution | |
|---|---|---|
| 10 | 19 | |
| 5,671 | 4,499 | |
| - | 0.8% | |
| 3.4 | 0.0 | |
| 7 days ago | about 2 months ago | |
| Jupyter Notebook | Python | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
t81_558_deep_learning
Posts with mentions or reviews of t81_558_deep_learning.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-02-27.
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Wednesday Daily Thread: Beginner questions
I am just getting into Machine Learning with Python. I have an M1 MacBook Air and (somehow) managed to install Tensorflow according to this tutorial https://github.com/jeffheaton/t81_558_deep_learning/blob/master/install/tensorflow-install-mac-metal-jul-2021.ipynb , which is apparently the bread and butter of machine learning.
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Install Tensorflow through Miniforge on M1 Mac
I skimmed through other forums and they suggest using Miniforge instead of Anaconda. Specifically, I was following this guide: https://github.com/jeffheaton/t81_558_deep_learning/blob/master/install/tensorflow-install-mac-metal-jul-2021.ipynb
- Does anyone have Keras for image classification up and running on a Mac?
- layers.Conv2D( ) -> Running this function kills the Python Kernel
- Different Outputs on Mac M1 and Windows
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Learning Roadmap for Beginners in ML (I'm following it). What do you guys think about it?
Applications of Deep Neural Networks with Keras (2021), by Jeff Heaton https://sites.wustl.edu/jeffheaton/t81-558/ https://arxiv.org/pdf/2009.05673.pdf
- i figured out how to animate the GAN i've been training!
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D Simple Questions Thread December 20 2020
dnnlib.SubmitConfig clearly does not exist in that version of dnnlib, and looks to have never existed in the NVlabs/stylegan2-ada repository. However, it does exist in the NVlabs/stylegan2 repository. My hunch is that the code was haphazardly ported from StyleGAN2 to the newer StyleGAN2-ADA, and it is simply an oversight after porting. There is an issue in the jeffheaton/t81_558_deep_learning repository (I assume you are you eluzzi5?), so I'll add this info to that issue.
I am using the following code to try to run StyleGAN on Google Colab: https://github.com/jeffheaton/t81_558_deep_learning/blob/master/t81_558_class_07_3_style_gan.ipynb
image-super-resolution
Posts with mentions or reviews of image-super-resolution.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-12-15.
- A tech worker is selling a children's book he made using AI. Professional illustrators are pissed.
- Low quality surveillance footage from a hit and run that happened today. Greatly appreciate if anyone has any ideas on how to get the plate number.
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[R] What are the best pretrained super-resolution GAN models on GitHub?
Currently, I have already implemented the pretrained GAN model from here, however I am not yet satisfied with the results. Indeed, I will go with this one if there's no other option, but I was hoping maybe someone here can point me to a better direction. Thank you!
- [P] Tutorial on using image super-resolution without Photoshop
- [P] Tutorial on how to use image super-resolution without photoshop
- What’s an extremely useful website most people probably don’t know about?
- Hit and Run Can someone help me figure out what the plate says? Also any advice I've never been in an accident before
- VC#4 - pancake - vc.ajmoon.uk - VQGAN/CLIP + 3D Photo Inpainting + Image Super-Resolution
What are some alternatives?
When comparing t81_558_deep_learning and image-super-resolution you can also consider the following projects:
dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).
SwinIR - SwinIR: Image Restoration Using Swin Transformer (official repository)
DotA2-Icon-GAN - Using GANs to generate DotA2 Ability Icons
VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
Hands-On-Meta-Learning-With-Python - Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow
video2x - A lossless video/GIF/image upscaler achieved with waifu2x, Anime4K, SRMD and RealSR. Started in Hack the Valley II, 2018.
Artifact_Removal_GAN - A U-net GAN for jpeg artifact removal
DeepCreamPy - Decensoring Hentai with Deep Neural Networks
handwritten-digits-recognizer-webapp - This is my first experience with machine learning
waifu2x - Image Super-Resolution for Anime-Style Art
gan-vae-pretrained-pytorch - Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.
MAX-Image-Resolution-Enhancer - Upscale an image by a factor of 4, while generating photo-realistic details.
t81_558_deep_learning vs dnn_from_scratch
image-super-resolution vs SwinIR
t81_558_deep_learning vs DotA2-Icon-GAN
image-super-resolution vs VQGAN-CLIP
t81_558_deep_learning vs Hands-On-Meta-Learning-With-Python
image-super-resolution vs video2x
t81_558_deep_learning vs Artifact_Removal_GAN
image-super-resolution vs DeepCreamPy
t81_558_deep_learning vs handwritten-digits-recognizer-webapp
image-super-resolution vs waifu2x
t81_558_deep_learning vs gan-vae-pretrained-pytorch
image-super-resolution vs MAX-Image-Resolution-Enhancer