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app.py

@@ -18,7 +18,7 @@ from utils.paramUtil import t2m_kinematic_chain
 clip_version = 'ViT-B/32'
 
 class MotionGenerator:
-    def __init__(self, checkpoints_dir, dataset_name, model_name, res_name, vq_name, device='cuda'):
+    def __init__(self, checkpoints_dir, dataset_name, model_name, res_name, vq_name, device='auto'):
         self.device = torch.device(device if torch.cuda.is_available() else 'cpu')
         self.dataset_name = dataset_name
         self.dim_pose = 251 if dataset_name == 'kit' else 263
@@ -250,15 +250,10 @@ class MotionGenerator:
 def create_gradio_interface(generator, output_dir='./gradio_outputs'):
     os.makedirs(output_dir, exist_ok=True)
 
-    def generate_motion(text_prompt, progress=gr.Progress()):
+    def generate_motion(text_prompt):
         try:
-            import time
-            start_time = time.time()
-
-            print(f"\n{'='*70}")
-            print(f"[START] Generating motion for: '{text_prompt}'")
+            print(f"\nGenerating motion for: '{text_prompt}'")
             print(f"Device: {generator.device}")
-            print(f"{'='*70}")
 
             # Use default parameters for simplicity
             motion_length = 0  # Auto-estimate
@@ -270,15 +265,7 @@ def create_gradio_interface(generator, output_dir='./gradio_outputs'):
             seed = 42
             use_ik = True
 
-            # Show warning about CPU
-            if str(generator.device) == 'cpu':
-                print("\n⚠️  WARNING: Using CPU - this will take 10-30 minutes!")
-                print("For faster inference, upgrade Space to GPU hardware.")
-
             # Generate motion
-            progress(0.1, desc="[1/4] Generating motion tokens (10-20 mins on CPU)...")
-            print("[1/4] Generating motion tokens...")
-
             joint, actual_length = generator.generate(
                 text_prompt,
                 motion_length,
@@ -290,13 +277,7 @@ def create_gradio_interface(generator, output_dir='./gradio_outputs'):
                 seed
             )
 
-            elapsed = time.time() - start_time
-            print(f"✓ Generated {actual_length} frames in {elapsed:.1f}s")
-
             # Save BVH and video
-            progress(0.6, desc="[2/4] Converting to BVH format...")
-            print("[2/4] Converting to BVH format...")
-
             timestamp = str(np.random.randint(100000))
             video_path = pjoin(output_dir, f'motion_{timestamp}.mp4')
 
@@ -305,32 +286,17 @@ def create_gradio_interface(generator, output_dir='./gradio_outputs'):
                 joint, filename=None, iterations=100, foot_ik=True
             )
 
-            print("✓ BVH conversion complete")
-
             # Create video
-            progress(0.8, desc="[3/4] Rendering video...")
-            print("[3/4] Rendering video...")
-
             plot_3d_motion(video_path, generator.kinematic_chain, joint_processed,
                           title=text_prompt, fps=20)
 
-            print(f"✓ Video saved: {video_path}")
-
-            progress(1.0, desc="[4/4] Complete!")
-            total_time = time.time() - start_time
-            print(f"[4/4] Complete! Total time: {total_time:.1f}s")
-            print(f"{'='*70}\n")
-
+            print(f"Video saved: {video_path}")
             return video_path
 
         except Exception as e:
             import traceback
             error_msg = f"Error: {str(e)}\n\nTraceback:\n{traceback.format_exc()}"
-            print("="*70)
-            print("ERROR during generation:")
-            print("="*70)
             print(error_msg)
-            print("="*70)
             return None
     
     # Create Gradio interface with Blocks for custom layout
@@ -372,17 +338,6 @@ def create_gradio_interface(generator, output_dir='./gradio_outputs'):
         
         gr.Markdown("# 🎭 Text-to-Motion Generator")
         gr.Markdown("Generate 3D human motion animations from text descriptions")
-
-        # Show CPU warning if applicable
-        device_str = str(generator.device)
-        if 'cpu' in device_str:
-            gr.Markdown("""
-            ### ⚠️ Performance Notice
-            This Space is running on **CPU** (free tier). Generation takes **15-30 minutes** per prompt.
-            Please be patient! For faster results (~30 seconds), upgrade to GPU in Space Settings.
-            """)
-        else:
-            gr.Markdown(f"### ✅ Running on: {device_str.upper()}")
         
         with gr.Row():
             with gr.Column():
@@ -432,7 +387,7 @@ if __name__ == '__main__':
         model_name=MODEL_NAME,
         res_name=RES_NAME,
         vq_name=VQ_NAME,
-        device='cuda'
+        device='auto'
     )
     
     # Create and launch Gradio interface