import torch from PIL import Image from RealESRGAN import RealESRGAN import gradio as gr device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') print(device) model2 = RealESRGAN(device, scale=2) model2.load_weights('weights/RealESRGAN_x2.pth', download=True) model4 = RealESRGAN(device, scale=4) model4.load_weights('weights/RealESRGAN_x4.pth', download=True) model8 = RealESRGAN(device, scale=8) model8.load_weights('weights/RealESRGAN_x8.pth', download=True) def inference(image, size): if size == '2x': result = model2.predict(image.convert('RGB')) elif size == '4x': result = model4.predict(image.convert('RGB')) else: result = model8.predict(image.convert('RGB')) if torch.cuda.is_available(): torch.cuda.empty_cache() return result title = "Face Real ESRGAN UpScale: 2x 4x 8x" description = "This is an unofficial demo for Real-ESRGAN. Scales the resolution of a photo. This model shows better results on faces compared to the original version." article = "