Update app.py

app.py

@@ -21,7 +21,7 @@ def inference(img):
 
 title = "SUNet: Swin Transformer with UNet for Image Denoising"
 description = "Gradio demo for SUNet. SUNet has competitive performance results in terms of quantitative metrics and visual quality. See the paper and project page for detailed results below. Here, we provide a demo for AWGN image denoising. To use it, simply upload your image, or click one of the examples to load them. Reference from: https://huggingface.co/akhaliq"
-article = "<p style='text-align: center'><a href='https://' target='_blank'>SUNet: Swin Transformer with UNet for Image Denoising</a> | <a href='https://github.com/FanChiMao/SUNet' target='_blank'>Github Repo</a></p> <center><img src='https://visitor-badge.glitch.me/badge?page_id=52Hz_SUNet_AWGN_denoising' alt='visitor badge'></center>"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2202.14009' target='_blank'>SUNet: Swin Transformer with UNet for Image Denoising</a> | <a href='https://github.com/FanChiMao/SUNet' target='_blank'>Github Repo</a></p> <center><img src='https://visitor-badge.glitch.me/badge?page_id=52Hz_SUNet_AWGN_denoising' alt='visitor badge'></center>"
 
 examples = [['set5/baby.png'], ['set5/bird.png'],['set5/butterfly.png'],['set5/head.png'],['set5/woman.png']]
 gr.Interface(