updates

app.py

@@ -1,8 +1,8 @@
 """
 SHARP Gradio Demo
-- Standard Native Layout (No Custom CSS)
-- Two-Column Split
-- Clean Grouping for reduced congestion
+- Standard Native Layout
+- Fixed: Added @spaces.GPU for ZeroGPU compatibility (Fixes 'dummy' output)
+- Fixed: Download Button visibility logic
 """
 
 from __future__ import annotations
@@ -13,7 +13,17 @@ from pathlib import Path
 from typing import Final
 import gradio as gr
 
-# Suppress internal warnings to keep logs clean
+# --- 1. Import Spaces for ZeroGPU Support ---
+try:
+    import spaces
+except ImportError:
+    # Fallback for local testing if spaces is not installed
+    class spaces:
+        @staticmethod
+        def GPU(func):
+            return func
+
+# Suppress internal warnings
 warnings.filterwarnings("ignore", category=FutureWarning, module="torch.distributed")
 
 # Ensure model_utils is present in your directory
@@ -31,7 +41,7 @@ EXAMPLES_DIR: Final[Path] = ASSETS_DIR / "examples"
 IMAGE_EXTS: Final[tuple[str, ...]] = (".png", ".jpg", ".jpeg", ".webp")
 
 # -----------------------------------------------------------------------------
-# SEO (Meta Tags Only)
+# SEO
 # -----------------------------------------------------------------------------
 
 SEO_HEAD = """
@@ -74,6 +84,8 @@ def get_example_files() -> list[list[str]]:
             examples.append([str(img)])
     return examples
 
+# --- 2. Apply @spaces.GPU Decorator ---
+@spaces.GPU(duration=120) 
 def run_sharp(
     image_path: str | None,
     trajectory_type: str,
@@ -82,9 +94,10 @@ def run_sharp(
     fps: int,
     render_video: bool,
     progress=gr.Progress()
-) -> tuple[str | None, str | None, str]:
+) -> tuple[str | None, dict, str]:
     """
     Main Inference Function
+    Decorated with @spaces.GPU to ensure it runs on the GPU node.
     """
     if not image_path:
         raise gr.Error("Please upload an image first.")
@@ -92,12 +105,17 @@ def run_sharp(
     # Validate inputs
     out_long_side_val = None if int(output_long_side) <= 0 else int(output_long_side)
     
-    # Convert trajectory string to Enum or pass as is
-    traj_enum = TrajectoryType[trajectory_type.upper()] if hasattr(TrajectoryType, trajectory_type.upper()) else trajectory_type
+    # Convert trajectory string to Enum safely
+    traj_key = trajectory_type.upper()
+    if hasattr(TrajectoryType, traj_key):
+        traj_enum = TrajectoryType[traj_key]
+    else:
+        traj_enum = trajectory_type
 
     try:
-        progress(0.1, desc="Initializing SHARP model...")
+        progress(0.1, desc="Initializing SHARP model on GPU...")
         
+        # Call the backend model
         video_path, ply_path = predict_and_maybe_render_gpu(
             image_path,
             trajectory_type=traj_enum,
@@ -107,37 +125,48 @@ def run_sharp(
             render_video=bool(render_video),
         )
 
-        status_msg = f"### ✅ Success\nPLY: `{ply_path.name}`"
+        # Prepare outputs
+        status_msg = f"### ✅ Success\nGenerated: `{ply_path.name}`"
+        
+        video_result = str(video_path) if video_path else None
         if video_path:
             status_msg += f"\nVideo: `{video_path.name}`"
+
+        # Explicitly update the Download Button
+        download_btn_update = gr.DownloadButton(
+            value=str(ply_path), 
+            visible=True,
+            label=f"Download {ply_path.name}"
+        )
         
         return (
-            str(video_path) if video_path else None,
-            str(ply_path),
+            video_result,
+            download_btn_update,
             status_msg
         )
 
     except Exception as e:
-        raise gr.Error(f"Error: {str(e)}")
+        # If it fails, we return None for video, hide button, and show error
+        return (
+            None, 
+            gr.DownloadButton(visible=False), 
+            f"### ❌ Error\n{str(e)}"
+        )
 
 # -----------------------------------------------------------------------------
 # UI Construction
 # -----------------------------------------------------------------------------
 
 def build_demo() -> gr.Blocks:
-    # Use standard theme. 
-    # To reduce congestion further, you could try `theme=gr.themes.Soft()` or `Base()`
     theme = gr.themes.Default()
 
     with gr.Blocks(theme=theme, head=SEO_HEAD, title="SHARP 3D Generator") as demo:
         
-        # --- Header ---
         with gr.Row():
             with gr.Column(scale=1):
                 gr.Markdown("# SHARP: Single-Image 3D Generator\nConvert any static image into a 3D Gaussian Splat scene instantly.")
 
         # --- Main Layout (Strict Two Columns) ---
-        # Removed 'variant="panel"' to remove the grey box/padding that restricts width
         with gr.Row(equal_height=False):
             
             # --- LEFT COLUMN: Input & Controls ---
@@ -149,7 +178,7 @@ def build_demo() -> gr.Blocks:
                     interactive=True
                 )
 
-                # Settings grouped cleanly below image
+                # Configs
                 with gr.Group():
                     with gr.Row():
                         trajectory = gr.Dropdown(
@@ -185,19 +214,20 @@ def build_demo() -> gr.Blocks:
 
             # --- RIGHT COLUMN: Output ---
             with gr.Column(scale=1):
-                # Removed fixed height so it fills the column naturally
                 video_out = gr.Video(
                     label="3D Preview", 
                     autoplay=True,
-                    elem_id="output-video"
+                    elem_id="output-video",
+                    interactive=False
                 )
                 
                 with gr.Group():
                     status_md = gr.Markdown("Ready to generate.")
+                    # Button starts hidden
                     ply_download = gr.DownloadButton(
                         label="Download .PLY File",
                         variant="secondary",
-                        visible=True
+                        visible=False
                     )
 
         # --- Logic Binding ---