add about

app.py

@@ -1284,10 +1284,18 @@ with demo:
         buttons[-1].click(fn=lambda x: gr.update(visible=False), outputs=buttons[-1])
     
     
-    
+    with gr.Tab('About'):
+        gr.Markdown("##### This demo is for python package `ncut-pytorch`, please visit the [Documentation](https://ncut-pytorch.readthedocs.io/) ")
+        gr.Markdown("---")
+        gr.Markdown("**Normalized Cuts**, aka. spectral clustering, is a graphical method to analyze data grouping in the affinity eigenvector space. It has been widely used for unsupervised segmentation in the 2000s.")
+        gr.Markdown("---")        
+        gr.Markdown("##### We have implemented NCut, with some advanced features:")
+        gr.Markdown("- **Nyström** Normalized Cut, is a new approximation algorithm developed for large-scale graph cuts, a large-graph of million nodes can be processed in under 10s (cpu) or 2s (gpu).")
+        gr.Markdown("- **spectral-tSNE** visualization, a new method to visualize the high-dimensional eigenvector space with 3D RGB cube. Color is aligned across images, color infers distance in representation.")
+        
     with gr.Row():
         with gr.Column():
-            gr.Markdown("##### POWERED BY `ncut-pytorch`, [Documentation](https://ncut-pytorch.readthedocs.io/) ")
+            gr.Markdown("##### This demo is for `ncut-pytorch`, [Documentation](https://ncut-pytorch.readthedocs.io/) ")
         with gr.Column():
             gr.Markdown("###### Running out of GPU? Try [Demo](https://ncut-pytorch.readthedocs.io/en/latest/demo/) hosted at UPenn")