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.
Model source
- Kind
- Other
- File size
- 63.9–64.1 MB
- Version
- vRevision 8110204
- Updated
- Oct 20, 2026
- Downloads
- 0
- Source
- Hugging Face
Source description
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.
Real-ESRGAN is an upgraded ESRGAN trained with pure synthetic data is capable of enhancing details while removing annoying artifacts for common real-world images.
Usage
Code for using model you can obtain in our repo.
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', download=True)
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')
Sources
1 source
Sources
1 sourceVerified Oct 20
Download files
Model artifacts
3 artifacts
Model artifacts
3 artifactsSource excerpts
3 excerpts
Source excerpts
3 excerpts--- language: - ru - en tags: - PyTorch thumbnail: "https://github.com/sberbank-ai/Real-ESRGAN" --- # 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. Real-ESRGAN is an upgraded ESRGAN trained with pure synthetic data is capable of enhancing details while removing annoying artifacts for common real-world images. - [Paper](https://arxiv.org/abs/2107.10833) - [Original implementation](https://github.com/xinntao/Real-ESRGAN) - [Our github](https://github.com/sberbank-ai/Real-ESRGAN) ## Usage Code for using model you can obtain in our [repo](https://github.com/sberbank-ai/Real-ESRGAN). ```python 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', download=True) 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') ```
Source context: 0 downloads · 266 likes · Repo ai-forever/Real-ESRGAN
Source context: 0 downloads · 251 likes · Repo ai-forever/Real-ESRGAN
