a-PyTorch-Tutorial-to-Super-Resolution
mmagic
| a-PyTorch-Tutorial-to-Super-Resolution | mmagic | |
|---|---|---|
| 2 | 5 | |
| 542 | 6,588 | |
| - | 1.3% | |
| 2.7 | 8.7 | |
| about 1 year ago | about 2 months ago | |
| Python | Jupyter Notebook | |
| MIT License | Apache License 2.0 |
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.
a-PyTorch-Tutorial-to-Super-Resolution
-
What subjects in Python do you need to know to tackle Artificial Intelligence?
Image upscaling might be a good goal to work towards first, and there are probably lots of good tutorials on it. You can follow a tutorial and Google anything from the tutorial that you don't understand. Here's one I found that looks helpful at first glance, and it includes working code: https://github.com/sgrvinod/a-PyTorch-Tutorial-to-Super-Resolution
-
I have dozens of blurred images cropped from a custom YOLOv3 detection - What GAN can I use to reconstruct a single superior image?
Hi try to give a look at image super resolution task https://github.com/sgrvinod/a-PyTorch-Tutorial-to-Super-Resolution . This is the first result from google. Of course the quality of the results could depend on your data (domain shift). In that case grab high quality images from internet, lower their quality and do fine tuning of the selected model
mmagic
- More than Editing, Unlock the Magic!
-
MMEditing v1.0.0rc4 has been released （including Disco-Diffusion）
Join us to make it better! Try at https://github.com/open-mmlab/mmediting/tree/1.x
-
MMDeploy: Deploy All the Algorithms of OpenMMLab
MMEditing: OpenMMLab image and video editing toolbox.
What are some alternatives?
Real-ESRGAN - Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
Fast-SRGAN - A Fast Deep Learning Model to Upsample Low Resolution Videos to High Resolution at 30fps
Image-Super-Resolution-via-Iterative-Refinement - Unofficial implementation of Image Super-Resolution via Iterative Refinement by Pytorch
Real-ESRGAN-colab - A Real-ESRGAN model trained on a custom dataset
AnimeGAN - Generating Anime Images by Implementing Deep Convolutional Generative Adversarial Networks paper
cnn-watermark-removal - Fully convolutional deep neural network to remove transparent overlays from images
iSeeBetter - iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press
Deep-Exemplar-based-Video-Colorization - The source code of CVPR 2019 paper "Deep Exemplar-based Video Colorization".
pytorch-gans - PyTorch implementation of GANs (Generative Adversarial Networks). DCGAN, Pix2Pix, CycleGAN, SRGAN
contrastive-unpaired-translation - Contrastive unpaired image-to-image translation, faster and lighter training than cyclegan (ECCV 2020, in PyTorch)