Image Super-Resolution Using ESRGAN
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Updated
Aug 9, 2023 - Jupyter Notebook
Image Super-Resolution Using ESRGAN
A repository of models trained by me!
WindSR Dataset contains more than 22,000 pairs of HR/LR wind speed images, which are processed using the NASA's GEOS-5 Nature Run dataset. This dataset is useful for studying super-resolution for data collected using satellites rather natural RGB images.
Medal of Honor Allied Assault automated textures upscaling based on ESRGAN
Readme file is inside the project folder itself. This repository contains SRGAN and ESRGAN with their model cards and training files. This was a final project of the course EE541 from USC.
Research on ESRGAN (Enhanced Super-Resolution Generative Adversarial Networks, published in ECCV 2018), implemented in Tensorflow 2.0. All implementation deployed on Google Colab, and make some modify with origin Architecture include Losses.
This is an implementation of ESRGAN's in Tensorflow2.0/Keras.
Super resolution of DSM
VisionSoC - an Image Upscaling Project by Team SquadofCreators. It used ESRGAN as it model and flask to connect to its frontend. It has been Recognized as the runner up in the Paper Presentation event conducted by JCT College of Engineering.
This is the PyTorch implementation of ESRGAN .
This is the repository for my final project to predict batik textile's origin by its extracted color coordinat using Neural Networks Model
使用Vue和Real-ESRGAN的图片放大(清晰化)工具
Image Pearer automates the creation of image pairs from a LR and a HR source for neural network model training.
MXNet sample for super resolution
Image and Video Super Resolution
Using Computer Vision, ML, ESRGAN, and Image Processing to find the best sunsets across the ocean.
this simple image upscaling Django website uses esrgan algorithm to enhance and increase the resolution of images
Quake 2 textures upscaled using ESRGAN and the Manga109Attempt model
Repository for (Un)Clear SoC Project, done in the Summer of 2021.
Pumps up the Image resolution by x4 factor
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