modified app.py

app.py

@@ -1,3 +1,4 @@
+import spaces
 import cv2
 import numpy as np
 import gradio as gr
@@ -85,6 +86,12 @@ import os
 # preloaded_images = load_preuploaded_images()
 #
 # print("Preloaded images:", preloaded_images)
+@spaces.GPU
+def get_c(x, points):
+    with torch.no_grad():
+        counterfactual = model.get_counterfactual(x, points)
+    return counterfactual
+
 with gr.Blocks() as demo:
     with gr.Row():
         gr.Markdown('''# Generate interventions!🚀
@@ -268,8 +275,9 @@ with gr.Blocks() as demo:
 
             # Imagenet-normalize the inputs (standardization)
             x = utils.imagenet_normalize(x).to(device)
-            with torch.no_grad():
-                counterfactual = model.get_counterfactual(x, points)
+
+            counterfactual = get_c(x, points)
+
 
             counterfactual = counterfactual.squeeze()
 
@@ -286,4 +294,4 @@ with gr.Blocks() as demo:
 
 
     # Launch the app
-demo.queue().launch(inbrowser=True, share=True)
+demo.queue().launch()