add markdown

app.py

@@ -393,14 +393,24 @@ def preprocess_example(example_list):
     
 
 with gr.Blocks() as demo:
-   
+    
+    gr.Markdown(value='# Prithvi image reconstruction demo')
+    gr.Markdown(value='''Prithvi is a first-of-its-kind temporal Vision transformer pretrained by the IBM and NASA team on continental US Harmonised 
+    Landsat Sentinel 2 (HLS) data. Particularly, the model adopts a self-supervised encoder developed with a ViT architecture and Masked AutoEncoder 
+    learning strategy, with a MSE as a loss function. The model includes spatial attention across multiple patchies and also temporal attention for 
+    each patch. More info about the model and its weights are available [here](https://huggingface.co/ibm-nasa-geospatial/Prithvi-100M).\n
+    This demo showcases the image reconstracting over three timestamps, with the user providing a set of three HLS images and the model randomly masking 
+    out some proportion of the images and then reconstructing them based on the not masked portion of the images.\n
+    The user needs to provide three HLS geotiff images, including the following channels: Blue, Green, Red, NIRa, SWIR, SWIR 2.
+
+    ''')
     with gr.Row():
         with gr.Column():
             inp_files = gr.Files(elem_id='files')
             # inp_slider = gr.Slider(0, 100, value=50, label="Mask ratio", info="Choose ratio of masking between 0 and 100", elem_id='slider'),
             btn = gr.Button("Submit")
     with gr.Row():
-        gr.Markdown(value='Original images')
+        gr.Markdown(value='## Original images')
     with gr.Row():
         gr.Markdown(value='T1')
         gr.Markdown(value='T2')
@@ -410,7 +420,7 @@ with gr.Blocks() as demo:
         out2_orig_t2 = gr.Image(image_mode='RGB')
         out3_orig_t3 = gr.Image(image_mode='RGB')
     with gr.Row():
-        gr.Markdown(value='Masked images')
+        gr.Markdown(value='## Masked images')
     with gr.Row():
         gr.Markdown(value='T1')
         gr.Markdown(value='T2')
@@ -420,7 +430,7 @@ with gr.Blocks() as demo:
         out5_masked_t2 = gr.Image(image_mode='RGB')
         out6_masked_t3 = gr.Image(image_mode='RGB')
     with gr.Row():
-        gr.Markdown(value='Reonstructed images')
+        gr.Markdown(value='## Reonstructed images')
     with gr.Row():
         gr.Markdown(value='T1')
         gr.Markdown(value='T2')