Update app.py

app.py

@@ -1,3 +1,4 @@
+import spaces
 import gradio as gr
 import torch
 import cv2
@@ -21,6 +22,7 @@ from huggingface_hub import snapshot_download
 import subprocess
 import sys
 
+@spaces.GPU(duration=120)
 def download_liveportrait():
     """
     Clone the LivePortrait repository and prepare its dependencies.
@@ -55,6 +57,7 @@ def download_liveportrait():
         print("Failed to initialize LivePortrait:", e)
         raise
 
+@spaces.GPU(duration=120)
 def download_huggingface_resources():
     """
     Download additional necessary resources from Hugging Face using the CLI.
@@ -81,6 +84,7 @@ def download_huggingface_resources():
         print("General error in downloading resources:", e)
         raise
 
+@spaces.GPU(duration=120)
 def get_project_root():
     """Get the root directory of the current project."""
     return os.path.abspath(os.path.dirname(__file__))
@@ -116,9 +120,11 @@ pipe_controlnet.enable_attention_slicing()
 pipe_inpaint_controlnet.to(device)
 pipe_inpaint_controlnet.enable_attention_slicing()
 
+@spaces.GPU(duration=120)
 def resize_to_multiple_of_64(width, height):
     return (width // 64) * 64, (height // 64) * 64
 
+@spaces.GPU(duration=120)
 def expand_mask(mask, kernel_size):
     mask_array = np.array(mask)
     structuring_element = np.ones((kernel_size, kernel_size), dtype=np.uint8)
@@ -127,6 +133,7 @@ def expand_mask(mask, kernel_size):
     ).astype(np.uint8) * 255
     return Image.fromarray(expanded_mask_array)
 
+@spaces.GPU(duration=120)
 def crop_face_to_square(image_rgb, padding_ratio=0.2):
     """
     Detects the face in the input image and crops an enlarged square region around it.
@@ -155,6 +162,7 @@ def crop_face_to_square(image_rgb, padding_ratio=0.2):
 
     return resized_image
 
+@spaces.GPU(duration=120)
 def spirit_animal_baseline(image_path, num_images = 4):
 
     image = cv2.imread(image_path)
@@ -235,6 +243,7 @@ def spirit_animal_baseline(image_path, num_images = 4):
 
     return prompt, generated_images
 
+@spaces.GPU(duration=120)
 def spirit_animal_with_background(image_path, num_images = 4):
 
     image = cv2.imread(image_path)
@@ -323,6 +332,8 @@ def spirit_animal_with_background(image_path, num_images = 4):
 
     return prompt, generated_images
 
+
+@spaces.GPU(duration=120)
 def generate_multiple_animals(image_path, keep_background=True, num_images = 4):
 
     image = cv2.imread(image_path)
@@ -443,6 +454,7 @@ def generate_multiple_animals(image_path, keep_background=True, num_images = 4):
 
     return formatted_prompts, generated_images
 
+@spaces.GPU(duration=120)
 def wait_for_file(file_path, timeout=500):
     """
     Wait for a file to be created, with a specified timeout.
@@ -459,6 +471,7 @@ def wait_for_file(file_path, timeout=500):
         time.sleep(0.5)  # Check every 0.5 seconds
     return True
 
+@spaces.GPU(duration=120)
 def generate_spirit_animal_video(driving_video_path):
     os.chdir(".")
     try:
@@ -516,6 +529,8 @@ def generate_spirit_animal_video(driving_video_path):
         print(f"Error occurred: {e}")
         return None
 
+
+@spaces.GPU(duration=120)
 def generate_spirit_animal(image, animal_type, background):
     if animal_type == "Single Animal":
         if background == "Preserve Background":
@@ -529,6 +544,8 @@ def generate_spirit_animal(image, animal_type, background):
             prompt, generated_images = generate_multiple_animals(image, keep_background=False)
     return prompt, generated_images
 
+
+@spaces.GPU(duration=120)
 def compress_video(input_path, output_path, target_size_mb):
     target_size_bytes = target_size_mb * 1024 * 1024
     temp_output = "./temp_compressed.mp4"
@@ -557,6 +574,7 @@ def compress_video(input_path, output_path, target_size_mb):
     else:
         shutil.move(temp_output, output_path)
 
+@spaces.GPU(duration=120)
 def process_video(video_file):
     
     # 初始化 LivePortrait