| --- |
| license: mit |
| language: |
| - en |
| tags: |
| - ESRGAN |
| - Real-ESRGAN |
| - Pytorch |
| - Image-to-Image |
| - Tensorflow_Lite |
| --- |
| ## ESRGAN_Model |
| This repository contains the ESRGAN (Enhanced Super-Resolution Generative Adversarial Network) model for high-quality image super-resolution. |
| ESRGAN improves low-resolution images by reconstructing finer details, making it suitable for applications in image enhancement, restoration, and detail recovery. |
| ## ESRGAN (Enhanced SRGAN) Using [:rocket: [[Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN)] Model. |
| |
| # Quick Test |
| ### Dependencies |
| - Python 3 |
| - [Pytorch >= 1.0](https://pytorch.org/) (CUDA version >= 7.5 if installing with CUDA.[More Details](https://pytorch.org/get-started/previous-versions/)) |
| - Python packages: ``` pip install numpy opencv-python ``` |
| ## Test Models |
| 1. Clone this github repo. |
| ``` |
| git clone https://huggingface.co/spedrox-sac/ESRGAN |
| cd ESRGAN |
| ``` |
| 2. Place your own low-resolution images in ```./LR``` folder. (There are two sample images - baboon and comic). |
| 3. I've downloaded and fine tuned the model. But you can download pretrained models from [Google Drive](https://drive.google.com/drive/u/0/folders/17VYV_SoZZesU6mbxz2dMAIccSSlqLecY) or [Baidu Drive](https://pan.baidu.com/s/1-Lh6ma-wXzfH8NqeBtPaFQ). Place the models in ```./models```. We provide two models with high perceptual quality and high PSNR performance (see [model list](https://github.com/xinntao/ESRGAN/tree/master/models)). |
| 4. Run test. We provide ESRGAN model and RRDB_PSNR model and you can config in the ```test.py```. |
| ``` |
| python test.py |
| ``` |
