Update app.py

app.py

@@ -21,7 +21,8 @@ def inference(truncation,seeds):
 title = "OCTaGAN"
 description = "Gradio demo for OCTaGAN. OCTaGAN is a GAN trained on wide-field corneal Optical Coherence Tomography (OCT) scans to generate cornea scans with a variety of pathologies (e.g.keratoconus disease) and surgical procedures (e.g. Implantable Collamer Lens (ICL) surgery, intrastromal corneal ring segment (ICRS) surgery, and Laser vision correction). OCTaGAN can be used for educational purposes as well as for generating training examples for ML algorithms."
 
-article = "<p style='text-align: center'><img src='https://visitor-badge.glitch.me/badge?page_id=AUBMC-AIM_octogan' alt='visitor badge'></center>"
+article = "<p style='text-align: center'><a href='https://cyrilzakka.github.io/radiology/2020/10/13/mammogenesis.html' target='_blank'>MammoGANesis: Controlled Generation of High-Resolution Mammograms for Radiology Education</a><center><a href='https://colab.research.google.com/drive/1vfbvMMkEBIwiuSbuC5pP-hsQr1nBmJXa?usp=sharing' target='_blank'><img src='https://colab.research.google.com/assets/colab-badge.svg' alt='Open In Colab'/></a></center></p><center><img src='https://visitor-badge.glitch.me/badge?page_id=AUBMC-AIM_octogan' alt='visitor badge'></center>"
+
 
 gr.Interface(inference,[gr.inputs.Slider(label="truncation",minimum=0, maximum=5, step=0.1, default=0.8),gr.inputs.Slider(label="Seed",minimum=0, maximum=1000, step=1, default=0)],"pil",title=title,description=description,article=article, examples=[
     [0.8,0]