Create app.py

app.py

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+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')