super-resolution
SRGAN
| super-resolution | SRGAN | |
|---|---|---|
| 2 | 1 | |
| 1,452 | 3,205 | |
| - | 0.6% | |
| 0.0 | 2.7 | |
| almost 2 years ago | 2 months ago | |
| Python | Python | |
| Apache License 2.0 | - |
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super-resolution
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Is it not possible to get good results in Deep Learning if dataset is small (1000 images)? [D]
https://github.com/krasserm/super-resolution (Super useful for me)
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How to train "models" for opensv edsr (iam super noob)
And thanks ! so it means that I need to train it with one of these trainers inside this project for example https://github.com/krasserm/super-resolution And that means that iam forced to use python (at least for training) but it's OK 🙃
SRGAN
What are some alternatives?
Fast-SRGAN - A Fast Deep Learning Model to Upsample Low Resolution Videos to High Resolution at 30fps
a-PyTorch-Tutorial-to-Super-Resolution - Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network | a PyTorch Tutorial to Super-Resolution
MIRNet-TFJS - TensorFlow JS models for MIRNet for low-light💡 image enhancement
TensorLayer - Deep Learning and Reinforcement Learning Library for Scientists and Engineers
TrainYourOwnYOLO - Train a state-of-the-art yolov3 object detector from scratch!
Hands-On-Meta-Learning-With-Python - Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow
fps_highlights - Make beautiful highlights from FPS vidéos
License-super-resolution - A License Plate Image Reconstruction Project in Tensorflow2
SinGAN - Official pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"
medicalAI - Medical-AI is a AI framework specifically for Medical Applications https://aibharata.github.io/medicalAI/