title

app.py

@@ -143,6 +143,15 @@ for img in imgs:
     ])
 
 with gr.Blocks() as demo:
+    with gr.Row():
+        gr.Markdown(
+        """
+        <center><h2>M3L</h2></center>
+        <center>Multi-modal teacher for Masked Modality Learning</center>
+        <br>
+        <center>Demo to visualize predictions from the Linear Fusion model trained with the vanilla Mean Teacher and the <a href='https://harshm121.github.io/projects/m3l.html'>M3L</a> framework when trained with 0.2% (98) labels. </center>
+        """
+        )
     with gr.Row():
         rgbinput = gr.Image(label="RGB Input").style(height=256, width=256)
         depthinput = gr.Image(label="Depth Input").style(height=256, width=256)
@@ -156,6 +165,13 @@ with gr.Blocks() as demo:
         classnameouptut = gr.Image(label="Classes").style(height=384, width=384)
     with gr.Row():
         examplesRow = gr.Examples(examples=examples, examples_per_page=10, inputs=[rgbinput, depthinput, modelcheck])
+    with gr.Row():
+        gr.Markdown(
+        """
+        Read more about [M3L](https://harshm121.github.io/projects/m3l.html)! 
+        """
+        )
     submit_btn.click(fn = predict, inputs = [rgbinput, depthinput, modelcheck], outputs = [mtoutput, m3loutput, classnameouptut])
 
+demo.queue(concurrency_count=3)
 demo.launch()