License-super-resolution
mmagic
| License-super-resolution | mmagic | |
|---|---|---|
| 7 | 5 | |
| 357 | 6,588 | |
| - | 1.3% | |
| 0.0 | 8.7 | |
| almost 4 years ago | about 2 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | Apache License 2.0 |
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License-super-resolution
- Unfall mit Fahrerflucht, AI-Upscaling?
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Anyone else in favor of a rule against “help me find this song/movie/book/whatever?”
Nah, the tools we have today go way beyond tweaking sharpness and brightness. We are basically at CSI levels in reality. For example: https://towardsdatascience.com/license-plate-image-enhancement-5a170475bec1
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Need help with License super resolution code
I need your help with this code: https://github.com/zzxvictor/License-super-resolution Because I dont understand any coding, And I really need this code to help a friend! So if you understand what to do, Please comment me :)
- Anyway to enhance a video/picture to figure out a license plate?
- (Spoilers TWOW) *Enhance* Help Us Decipher One page, Just ONE PAGE from THE WINDS OF WINTER!
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Help enhancing video to see license plate?
Imo, there is a miniscule probability that taking one of the frames just before the one with the pillar hiding the plate and trying this could work: https://github.com/zzxvictor/License-super-resolution
- Need help IDing plates from hit and run
mmagic
- More than Editing, Unlock the Magic!
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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
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MMDeploy: Deploy All the Algorithms of OpenMMLab
MMEditing: OpenMMLab image and video editing toolbox.
What are some alternatives?
super-resolution - Tensorflow 2.x based implementation of EDSR, WDSR and SRGAN for single image super-resolution
a-PyTorch-Tutorial-to-Super-Resolution - Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network | a PyTorch Tutorial to Super-Resolution
GFPGAN-for-Video-SR - A colab notebook for video super resolution using GFPGAN
Real-ESRGAN - Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
pix2seq - Pix2Seq codebase: multi-tasks with generative modeling (autoregressive and diffusion)
Image-Super-Resolution-via-Iterative-Refinement - Unofficial implementation of Image Super-Resolution via Iterative Refinement by Pytorch
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
Real-ESRGAN-colab - A Real-ESRGAN model trained on a custom dataset
cnn-watermark-removal - Fully convolutional deep neural network to remove transparent overlays from images
Deep-Exemplar-based-Video-Colorization - The source code of CVPR 2019 paper "Deep Exemplar-based Video Colorization".
contrastive-unpaired-translation - Contrastive unpaired image-to-image translation, faster and lighter training than cyclegan (ECCV 2020, in PyTorch)
mmselfsup - OpenMMLab Self-Supervised Learning Toolbox and Benchmark