fix

app.py

@@ -1,7 +1,19 @@
-import spaces  # ZeroGPU support - MUST be imported first!
+# Conditional import for ZeroGPU support
+import os
+if os.environ.get("SPACES_ZERO_GPU") is not None:
+    import spaces
+else:
+    # Create a dummy spaces decorator for non-ZeroGPU environments
+    class spaces:
+        @staticmethod
+        def GPU(*decorator_args, **decorator_kwargs):
+            def decorator(func):
+                def wrapper(*args, **kwargs):
+                    return func(*args, **kwargs)
+                return wrapper
+            return decorator
 
 import gradio as gr
-import os
 import numpy as np
 import yaml
 import cv2
@@ -32,7 +44,10 @@ if torch.cuda.is_available():
     print(f"   GPU device: {torch.cuda.get_device_name(0)}")
     print(f"   GPU count: {torch.cuda.device_count()}")
 else:
-    print("   ℹ️  GPU will be allocated on-demand (ZeroGPU mode)")
+    if os.environ.get("SPACES_ZERO_GPU"):
+        print("   ℹ️  ZeroGPU mode - GPU will be allocated on-demand")
+    else:
+        print("   ⚠️  No CUDA GPU detected - will use CPU")
 print("="*50)
 
 PROCESSED_VIDEO_DIR = './processed_videos'
@@ -186,7 +201,7 @@ def preview_crop(image_path, npy_file, video_path, expand_x, expand_y, offset_x,
     else:
         return None,None, "Failed to generate crop preview"
 
-@spaces.GPU(duration=120)  # Allocate GPU for 120 seconds (adjust based on your video length)
+@spaces.GPU(duration=300)
 def generate_video(input_img, should_crop_face, expand_x, expand_y, offset_x, offset_y, input_video_type, input_video, input_npy_select, input_npy, input_video_frames,
                    settings_steps, settings_cfg_scale, settings_seed, resolution_w, resolution_h,
                    model_step, custom_output_path, use_custom_fps, output_fps, callback_steps, context_frames, context_stride, context_overlap, context_batch_size, anomaly_action,intropolate_factor):
@@ -281,8 +296,10 @@ with gr.Blocks() as demo:
         gpu_name = torch.cuda.get_device_name(0)
         gpu_info = f"🚀 **GPU Enabled**: {gpu_name}"
     else:
-        # ZeroGPU mode - GPU allocated on-demand
-        gpu_info = "⚡ **ZeroGPU Mode**: GPU will be allocated automatically when generating"
+        if os.environ.get("SPACES_ZERO_GPU"):
+            gpu_info = "⚡ **ZeroGPU Mode**: GPU will be allocated when generating"
+        else:
+            gpu_info = "⚠️ **Running on CPU** (Generation will be slower)"
     
     gr.Markdown(f"<div style='text-align: center; padding: 10px; background-color: #e8f5e9; border-radius: 5px; border: 1px solid #4caf50;'>{gpu_info}</div>")