Update app.py

app.py

@@ -3,3 +3,46 @@ from PIL import Image
 from RealESRGAN import RealESRGAN
 import gradio as gr
 
+device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+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: Image, size: str) -> Image:
+    try:
+        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'))
+    except Exception as e:
+        print(e)
+        raise gr.Error(str(e))
+    return result
+
+
+title = "Face Real ESRGAN: 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.<br>Telegram BOT: https://t.me/restoration_photo_bot"
+article = "<div style='text-align: center;'>Twitter <a href='https://twitter.com/DoEvent' target='_blank'>Max Skobeev</a> | <a href='https://huggingface.co/sberbank-ai/Real-ESRGAN' target='_blank'>Model card</a>  <center><img src='https://visitor-badge.glitch.me/badge?page_id=max_skobeev_face_esrgan' alt='visitor badge'></center></div>"
+
+
+gr.Interface(inference,
+    [gr.Image(type="pil"), 
+    gr.Radio(['2x', '4x', '8x'], 
+    type="value",
+    value='2x',
+    label='Resolution model')], 
+    gr.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[['groot.jpeg', "2x"]],
+    allow_flagging='never',
+    theme="default",
+    cache_examples=False,
+    ).queue().launch(show_error=True)