aarbelle elischwartz commited on
Commit
8e2a7a5
1 Parent(s): a393337

Added more explanations (#2)

Browse files

- Added more explanations (e9278d2a154494eb2630ae212a8555847943f0a7)


Co-authored-by: Eli Schwartz <elischwartz@users.noreply.huggingface.co>

Files changed (1) hide show
  1. app.py +2 -1
app.py CHANGED
@@ -71,6 +71,7 @@ demo = gr.Blocks()
71
  with demo:
72
  gr.Markdown('# Unsupervised Domain Generalization by Learning a Bridge Across Domains')
73
  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)')
 
74
  gr.Markdown('## Instructions:')
75
  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.')
76
  gr.Markdown('## Select Query Domain: ')
@@ -85,7 +86,7 @@ with demo:
85
  with gr.Column():
86
  domain_drop = gr.Dropdown(domains, label='Domain')
87
  cl_drop = gr.Dropdown(class_list, label='Query Class')
88
- slider = gr.Slider(0, 100)
89
 
90
  # gr.Markdown('\t')
91
  # gr.Markdown('\t')
 
71
  with demo:
72
  gr.Markdown('# Unsupervised Domain Generalization by Learning a Bridge Across Domains')
73
  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)')
74
+ 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.')
75
  gr.Markdown('## Instructions:')
76
  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.')
77
  gr.Markdown('## Select Query Domain: ')
 
86
  with gr.Column():
87
  domain_drop = gr.Dropdown(domains, label='Domain')
88
  cl_drop = gr.Dropdown(class_list, label='Query Class')
89
+ slider = gr.Slider(0, 100, label='Query image selector slider')
90
 
91
  # gr.Markdown('\t')
92
  # gr.Markdown('\t')