last

app.py

@@ -5,7 +5,6 @@ import gradio as gr
 import os
 import spaces
 
-# Kiểm tra và cấu hình GPU
 if torch.cuda.is_available():
     print(f"CUDA is available. GPU: {torch.cuda.get_device_name(0)}")
     device = torch.device("cuda")
@@ -13,7 +12,6 @@ else:
     print("CUDA is not available. Using CPU.")
     device = torch.device("cpu")
 
-# Lazy loading cho các mô hình
 class LazyRealESRGAN:
     def __init__(self, device, scale):
         self.device = device
@@ -33,7 +31,6 @@ model2 = LazyRealESRGAN(device, scale=2)
 model4 = LazyRealESRGAN(device, scale=4)
 model8 = LazyRealESRGAN(device, scale=8)
 
-# Hàm inference chính
 @spaces.GPU
 def inference(image, size):
     if image is None:
@@ -60,12 +57,11 @@ def inference(image, size):
     except Exception as e:
         raise gr.Error(f"An error occurred: {str(e)}")
 
-# Cấu hình giao diện Gradio
 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 = "<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><div>"
 
-# Khởi tạo và chạy giao diện Gradio
+
+
 iface = gr.Interface(
     inference,
     [
@@ -75,11 +71,10 @@ iface = gr.Interface(
     gr.Image(type="pil", label="Output"),
     title=title,
     description=description,
-    #examples=[["groot.jpeg", "2x"]],
     flagging_mode="never",
     cache_examples=True
 )
 
-# Chạy ứng dụng
+
 if __name__ == "__main__":
     iface.launch(debug=True, show_error=True)