Update app.py

app.py

@@ -1,4 +1,4 @@
-import spaces
+#import spaces
 import contextlib
 import gc
 import json
@@ -173,7 +173,7 @@ examples = [
 global pipeline
 global MultiResNetModel
 
-@spaces.GPU
+#@spaces.GPU
 def load_ckpt(input_style):
     global pipeline
     global MultiResNetModel
@@ -264,7 +264,7 @@ cur_input_style = "GrayImage(ScreenStyle)"
 load_ckpt(cur_input_style)
 cur_input_style = None
 
-@spaces.GPU
+#@spaces.GPU
 def fix_random_seeds(seed):
     random.seed(seed)
     np.random.seed(seed)
@@ -280,7 +280,7 @@ def process_multi_images(files):
         imgs.append(img)
     return imgs 
 
-@spaces.GPU
+#@spaces.GPU
 def extract_lines(image):
     src = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2GRAY)
 
@@ -305,7 +305,7 @@ def extract_lines(image):
     torch.cuda.empty_cache()
     return outimg
 
-@spaces.GPU
+#@spaces.GPU
 def to_screen_image(input_image):
     global opt
     global ScreenModel
@@ -321,7 +321,7 @@ def to_screen_image(input_image):
     torch.cuda.empty_cache()
     return image_pil
 
-@spaces.GPU
+#@spaces.GPU
 def extract_line_image(query_image_, input_style, resolution):
     if resolution == "640x640":
         tar_width = 640
@@ -348,7 +348,7 @@ def extract_line_image(query_image_, input_style, resolution):
     torch.cuda.empty_cache()
     return input_context, extracted_line, input_context  
 
-@spaces.GPU(duration=180)
+#@spaces.GPU(duration=180)
 def colorize_image(VAE_input, input_context, reference_images, resolution, seed, input_style, num_inference_steps):
     if VAE_input is None or input_context is None:
         gr.Info("Please preprocess the image first")
@@ -543,4 +543,4 @@ with gr.Blocks() as demo:
     # )
 
     
-demo.launch()
+demo.launch(share = True)