Added more explanations (#2)

- Added more explanations (e9278d2a154494eb2630ae212a8555847943f0a7)


Co-authored-by: Eli Schwartz <[email protected]>

app.py

@@ -71,6 +71,7 @@ demo = gr.Blocks()
 with demo:
     gr.Markdown('# Unsupervised Domain Generalization by Learning a Bridge Across Domains')
     gr.Markdown('This demo showcases the cross-domain retrieval capabilities of our self-supervised cross domain training as presented @CVPR 2022. For details please refer to [the paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Harary_Unsupervised_Domain_Generalization_by_Learning_a_Bridge_Across_Domains_CVPR_2022_paper.pdf)')
+    gr.Markdown('The model is trained in an unsupervised manner on all domains without class labels. The labels are displayed to indicate retrieval success/failure.')
     gr.Markdown('## Instructions:')
     gr.Markdown('Select a query domain and a class from the drop-down menus and the select any random image from the domain using the slider below and press the "Run" button. The retrieved results from each of the four domains, along with the class label will be presented.')
     gr.Markdown('## Select Query Domain: ')
@@ -85,7 +86,7 @@ with demo:
         with gr.Column():
             domain_drop = gr.Dropdown(domains, label='Domain')
             cl_drop = gr.Dropdown(class_list,  label='Query Class')
-            slider = gr.Slider(0, 100)
+            slider = gr.Slider(0, 100, label='Query image selector slider')
 
         # gr.Markdown('\t')
         # gr.Markdown('\t')