nice

app.py

@@ -235,7 +235,7 @@ with gr.Blocks(theme="bethecloud/storj_theme", css=css) as demo:
                 step=1,
             )
             num_steps = gr.Slider(
-                label="Number of steps", minimum=1, maximum=100, value=15, step=1
+                label="Number of steps", minimum=1, maximum=100, value=12, step=1
             )  # 20/4.5 or 12 without lora, 4 with lora
             guidance_scale = gr.Slider(
                 label="Guidance scale", minimum=0.1, maximum=30.0, value=5.5, step=0.1
@@ -340,7 +340,7 @@ with gr.Blocks(theme="bethecloud/storj_theme", css=css) as demo:
     def turn_buttons_on():
         return gr.update(visible=True), gr.update(visible=True)
 
-@spaces.GPU(duration=12)
+@spaces.GPU(duration=6)
 @torch.inference_mode()
 def process_image(
     image,
@@ -356,16 +356,16 @@ def process_image(
     seed,
     progress=gr.Progress(track_tqdm=True)
 ):
+    preprocess_start = time.time()
     print("processing image")
-    start = time.time()
     preprocessor.load("NormalBae")
     # preprocessor.load("Canny") #20 steps, 9 guidance, 512, 512
-    
+
     global compiled
     if not compiled:
         print("Not Compiled")
         compiled = True
-        
+    
     seed = random.randint(0, MAX_SEED)
     generator = torch.cuda.manual_seed(seed)
     control_image = preprocessor(
@@ -373,12 +373,14 @@ def process_image(
         image_resolution=image_resolution,
         detect_resolution=preprocess_resolution,
     )
+    preprocess_time = time.time() - preprocess_start
     if style_selection is not None or style_selection != "None":
         prompt = "Photo from Pinterest of " + apply_style(style_selection) + " " + prompt + " " + a_prompt
     else:
         prompt=str(get_prompt(prompt, a_prompt))
     negative_prompt=str(n_prompt)
     print(prompt)
+    start = time.time()
     results = pipe(
         prompt=prompt,
         negative_prompt=negative_prompt,
@@ -388,7 +390,9 @@ def process_image(
         generator=generator,
         image=control_image,
     ).images[0]
-    print(f"\n-------------------------Processed in: {time.time() - start:.2f} seconds-------------------------")
+    torch.cuda.empty_cache()
+    print(f"\n-------------------------Preprocess done in: {preprocess_time:.2f} seconds-------------------------")    
+    print(f"\n-------------------------Inference done in: {time.time() - start:.2f} seconds-------------------------")
     
     # timestamp = int(time.time())
     #if not os.path.exists("./outputs"):