ESRGAN：Image Super Resolution
ESRGAN (Enhanced Super-Resolution Generative Adversarial Networks) is an efficient and user-friendly deep learning framework designed for performing image super-resolution tasks. It adopts a SRResNet-based architecture and incorporates residual, contextual loss, perceptual loss, and adversarial loss. The aim is to train the generator and discriminator networks to restore image details while making the generated images more realistic.
Source model
- Input shape: 128x128
- Number of parameters: 16.69M
- Model size: 63.8MB
- Output shape: 1x3x512x512
Source model repository: ESRGAN
Performance Reference
Please search model by model name in Model Farm
Inference & Model Conversion
Please search model by model name in Model Farm
License
Source Model: APACHE-2.0
Deployable Model: APLUX-MODEL-FARM-LICENSE
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
🙋
Ask for provider support