return the image actually

app.py

@@ -75,7 +75,7 @@ perceptor = (
     .requires_grad_(False)
     .to(device)
 )
-def run(user_input,num_steps, template, width,height):
+def run_all(user_input,num_steps, template, width,height):
     import random
     #if uploaded_file is not None:
         #uploaded_folder = f"{DefaultPaths.root_path}/uploaded"
@@ -1522,10 +1522,6 @@ def run(user_input,num_steps, template, width,height):
 
             except KeyboardInterrupt:
                 pass
-            except st.script_runner.StopException as e:
-                torch.cuda.empty_cache()
-                pass
-            return j
 
     def add_noise(img):
 
@@ -2297,10 +2293,11 @@ def run(user_input,num_steps, template, width,height):
             mh = ModelHost(args)
             x = 0
 
-            for x in range(batch_size):
-                mh.setup_model(x)
-                last_iter = mh.run(x)
-                x = x + 1
+            #for x in range(batch_size):
+            mh.setup_model(x)
+            last_iter = mh.run(x)
+            return(last_iter)
+            #x = x + 1
           
         if zoom:
             files = os.listdir(steps_path)
@@ -2326,7 +2323,7 @@ def run(user_input,num_steps, template, width,height):
 ##################### START GRADIO HERE ############################
 image = gr.outputs.Image(type="pil", label="Your result")
 iface = gr.Interface(
-    fn=run, 
+    fn=run_all, 
     inputs=[
     gr.inputs.Textbox(label="Prompt - try adding increments to your prompt such as 'oil on canvas', 'a painting', 'a book cover'",default="chalk pastel drawing of a dog wearing a funny hat"),
     gr.inputs.Slider(label="Steps - more steps can increase quality but will take longer to generate",default=45,maximum=50,minimum=1,step=1),