Update app.py

app.py

@@ -24,7 +24,9 @@ nb_samples = 500
 
 field_names_train = ["sig11", "sig22", "sig12", "U1", "U2", "q"]
 
-
+_HEADER_ = '''
+<h2><b>Visualization demo of <a href='https://huggingface.co/datasets/PLAID-datasets/Tensile2d' target='_blank'><b>Tensile2d dataset</b></b></h2>
+'''
 
 
 def sample_info(sample_id_str, fieldn):
@@ -82,7 +84,24 @@ def sample_info(sample_id_str, fieldn):
     
     str__ = f"Training sample {sample_id_str}\n"
     str__ += str(plaid_sample)+"\n"
-    str__ += f"number of nodes: {nodes.shape[0]}"
+    
+    if len(hf_dataset.description['in_scalars_names'])>0:        
+        str__ += "\ninput scalars:\n"
+        for sname in hf_dataset.description['in_scalars_names']:
+            str__ += f"- {sname}: {plaid_sample.get_scalar(sname)}\n"
+    if len(hf_dataset.description['out_scalars_names'])>0:        
+        str__ += "\noutput scalars:\n"
+        for sname in hf_dataset.description['out_scalars_names']:
+            str__ += f"- {sname}: {plaid_sample.get_scalar(sname)}\n"
+    str__ += f"\n\nMesh number of nodes: {nodes.shape[0]}\n"
+    if len(hf_dataset.description['in_fields_names'])>0:        
+        str__ += "\ninput fields:\n"
+        for fname in hf_dataset.description['in_fields_names']:
+            str__ += f"- {fname}\n"
+    if len(hf_dataset.description['out_fields_names'])>0:        
+        str__ += "\noutput fields:\n"
+        for fname in hf_dataset.description['out_fields_names']:
+            str__ += f"- {fname}\n"
 
     return str__, color
 
@@ -90,17 +109,17 @@ def sample_info(sample_id_str, fieldn):
 if __name__ == "__main__":
 
     with gr.Blocks() as demo:
-        d1 = gr.Slider(0, nb_samples-1, value=0, label="Training sample id", info="Choose between 0 and "+str(nb_samples-1))
-        d2 = gr.Dropdown(field_names_train, value=field_names_train[0], label="Field name")
-
-
-        output1 = gr.Text(label="Training sample info")
-        output2 = gr.Image(label="Training sample visualization")
-
-
+        gr.Markdown(_HEADER_)
+        with gr.Row(variant="panel"):
+            with gr.Column():
+                d1 = gr.Slider(0, nb_samples-1, value=0, label="Training sample id", info="Choose between 0 and "+str(nb_samples-1))
+                output1 = gr.Text(label="Training sample info")
+            with gr.Column():
+                d2 = gr.Dropdown(field_names_train, value=field_names_train[0], label="Field name")        
+                output2 = gr.Image(label="Training sample visualization")
+                
         d1.input(sample_info, [d1, d2], [output1, output2])
         d2.input(sample_info, [d1, d2], [output1, output2]) 
 
-
     demo.launch()