Update app.py

app.py

@@ -19,6 +19,12 @@ To do so, we first get our simulated images. After, we process these images to g
 
 Therefore, we are able to change our simulation texture, and still keeping the image composition.
 
+
+Our objectif for the sprint is to perform data augmentation using ControlNet. We then look for having a model that can augment an image quickly.
+For now, we benchmarked our model on a node of 4 Titan RTX 24Go. We were able to generate a batch of 4 images in a average time of 1.3 seconds!
+We also have access to nodes composed of 8 A100 80Go GPUs. The benchmark on one of these nodes will come soon.
+ 
+
 """
 
 
@@ -226,7 +232,10 @@ def create_demo(process, max_images=12, default_num_images=4):
         
         with gr.Row():
             gr.Markdown(description)
-        
+
+            gr.Video("./trajectory/trajectory.avi",
+                    format="avi",
+                    interactive=False)