Update app.py

app.py

@@ -1,4 +1,4 @@
-import spaces
+#import spaces
 import random
 import torch
 import cv2
@@ -85,7 +85,7 @@ pipe_depth.load_ip_adapter(f'{ckpt_dir_ipa}' , subfolder="", weight_name=["ip_ad
 pipe_canny.load_ip_adapter(f'{ckpt_dir_ipa}' , subfolder="", weight_name=["ip_adapter_plus_general.bin"])
 pipe_pose.load_ip_adapter(f'{ckpt_dir_ipa}' , subfolder="", weight_name=["ip_adapter_plus_general.bin"])
 
-@spaces.GPU
+#@spaces.GPU
 def process_canny_condition(image, canny_threods=[100,200]):
     np_image = image.copy()
     np_image = cv2.Canny(np_image, canny_threods[0], canny_threods[1])
@@ -96,7 +96,7 @@ def process_canny_condition(image, canny_threods=[100,200]):
 
 model_midas = MidasDetector()
 
-@spaces.GPU
+#@spaces.GPU
 def process_depth_condition_midas(img, res = 1024):
     h,w,_ = img.shape
     img = resize_image(HWC3(img), res)
@@ -105,7 +105,7 @@ def process_depth_condition_midas(img, res = 1024):
     return Image.fromarray(result)
 
 model_dwpose = DWposeDetector()
-@spaces.GPU
+#@spaces.GPU
 def process_dwpose_condition(image, res=1024):
     h,w,_ = image.shape
     img = resize_image(HWC3(image), res)
@@ -117,7 +117,7 @@ def process_dwpose_condition(image, res=1024):
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
 
-@spaces.GPU
+#@spaces.GPU
 def infer_depth(prompt, 
           image = None, 
           ipa_img = None,
@@ -154,7 +154,7 @@ def infer_depth(prompt,
     ).images[0]
     return [condi_img, image], seed
 
-@spaces.GPU
+#@spaces.GPU
 def infer_canny(prompt, 
           image = None, 
           ipa_img = None,
@@ -191,7 +191,7 @@ def infer_canny(prompt,
     ).images[0]
     return [condi_img, image], seed
 
-@spaces.GPU
+#@spaces.GPU
 def infer_pose(prompt, 
           image = None, 
           ipa_img = None,
@@ -388,4 +388,4 @@ with gr.Blocks(css=css) as Kolors:
         outputs = [result, seed_used]
     )
 
-Kolors.queue().launch(debug=True)
+Kolors.queue().launch(debug=True, share = True)