.

app.py

@@ -254,7 +254,11 @@ simple = pd.DataFrame(
 )
 
 with gr.Blocks() as demo:
-   
+    with gr.Row():
+        gr.Markdown(value='# Eclipse2')
+        gr.Button("Input")
+        gr.Button("Categories")
+        gr.Button("X")
     gr.Markdown(value='# Prithvi multi temporal crop classification')
     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. This demo showcases how the model was finetuned to classify crop and other land use categories using multi temporal data. More detailes can be found [here](https://huggingface.co/ibm-nasa-geospatial/Prithvi-100M-multi-temporal-crop-classification).\n
     The user needs to provide an HLS geotiff image, including 18 bands for 3 time-step, and each time-step includes the channels described above (Blue, Green, Red, Narrow NIR, SWIR, SWIR 2) in order.
@@ -265,31 +269,30 @@ with gr.Blocks() as demo:
             btn = gr.Button("Submit")
             
         with gr.Column():
-            inp1=gr.Image(image_mode='RGB', scale=10, label='T1')
-            inp2=gr.Image(image_mode='RGB', scale=10, label='T2')
-            inp3=gr.Image(image_mode='RGB', scale=10, label='T3')
-            out = gr.Image(image_mode='RGB', scale=10, label='Model prediction')
-            # gr.Image(value='Legend.png', image_mode='RGB', scale=2, show_label=False)
-    
+            with gr.Row():
+                inp1=gr.Image(image_mode='RGB', scale=10, label='T1')
+                inp2=gr.Image(image_mode='RGB', scale=10, label='T2')
+                inp3=gr.Image(image_mode='RGB', scale=10, label='T3')
+
     btn.click(fn=func, inputs=inp, outputs=[inp1, inp2, inp3, out])
 
     with gr.Row():
         with gr.Column():
-            with gr.Row():
-                gr.BarPlot(simple,
-                        x="a",
-                        y="b",
-                        title="Simple Bar Plot with made up data",
-                        tooltip=["a", "b"],
-                        y_lim=[20, 100],)
-            with gr.Row():
-                gr.LinePlot(simple,
-                            x='a',
-                            y='b')
-
+            gr.BarPlot(simple,
+                    x="a",
+                    y="b",
+                    title="Simple Bar Plot with made up data",
+                    tooltip=["a", "b"],
+                    y_lim=[20, 100],)
+            gr.LinePlot(simple,
+                        x='a',
+                        y='b')
         with gr.Column():
-            gr.Markdown(value='### Model prediction legend')
-            gr.Image(value='Legend.png', image_mode='RGB', show_label=False)
-    
+            out = gr.Image(image_mode='RGB', scale=10, label='Model prediction')
+            # gr.Image(value='Legend.png', image_mode='RGB', scale=2, show_label=False)
+  
+    with gr.Row():
+        gr.Markdown(value='### Model prediction legend')
+        gr.Image(value='Legend.png', image_mode='RGB', show_label=False)
 
-demo.launch() 
+demo.launch()