Real-ESRGAN

PyTorch implementation of a Real-ESRGAN model trained on custom dataset. This model shows better results on faces compared to the original version. It is also easier to integrate this model into your projects.

You can try it in google colab

Paper: Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data
Official github

Installation

Clone repo

git clone https://https://github.com/sberbank-ai/Real-ESRGAN
cd Real-ESRGAN

Install requirements
```
pip install -r requirements.txt
```
Download pretrained weights and put them into weights/ folder

Usage

Basic example:

import torch
from PIL import Image
import numpy as np
from realesrgan import RealESRGAN

device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')

model = RealESRGAN(device, scale=4)
model.load_weights('weights/RealESRGAN_x4.pth')

path_to_image = 'inputs/lr_image.png'
image = Image.open(path_to_image).convert('RGB')

sr_image = model.predict(image)

sr_image.save('results/sr_image.png')