Add spaces decorator for ZeroGPU

app.py

@@ -2,6 +2,7 @@ import gradio as gr
 import os
 import struct
 import numpy as np
+import spaces  # <--- 1. 新增這個 import
 
 # --- 1. Configuration ---
 SCENES = [
@@ -47,10 +48,9 @@ def read_gaussian_ply(filepath):
                 vertex_count = int(line.split()[-1])
                 break
         
-        print(f"Reading {vertex_count:,} Gaussian splats...")
+        print(f"Reading {vertex_count:,} Gaussian splats from {os.path.basename(filepath)}...")
         
         # 讀取二進制數據
-        # 每個 vertex: 17 個 float (x,y,z, nx,ny,nz, f_dc_0,f_dc_1,f_dc_2, opacity, scale*3, rot*4)
         bytes_per_vertex = 17 * 4  # 17 floats * 4 bytes
         data = f.read(vertex_count * bytes_per_vertex)
         
@@ -67,8 +67,6 @@ def read_gaussian_ply(filepath):
             vertices.append([x, y, z])
             
             # 提取顏色 (f_dc_0, f_dc_1, f_dc_2) 並轉換到 [0, 255]
-            # Gaussian Splatting 使用球諧函數,f_dc 是 DC 分量
-            # 轉換公式: color = (0.5 + SH_C0 * f_dc) * 255
             SH_C0 = 0.28209479177387814
             r = max(0, min(255, int((0.5 + SH_C0 * vertex_data[6]) * 255)))
             g = max(0, min(255, int((0.5 + SH_C0 * vertex_data[7]) * 255)))
@@ -101,75 +99,52 @@ def convert_to_standard_ply(input_path, output_path):
     
     print(f"✅ Converted to: {output_path}")
 
-# --- 4. 初始化 - 轉換所有文件 ---
-def initialize_converted_models():
-    """轉換所有 Gaussian Splatting PLY 為標準格式"""
+# --- 4. 核心處理函式 (加上 @spaces.GPU) ---
+# 注意：即使這只是檔案轉換，加上這個標籤可以解決 ZeroGPU 的檢查錯誤
+# 並且將運算移到計算節點上執行
+@spaces.GPU(duration=120) 
+def process_and_load_scene(evt: gr.SelectData):
+    index = evt.index
+    scene = SCENES[index]
     
     converted_dir = "converted"
     os.makedirs(converted_dir, exist_ok=True)
     
-    converted_scenes = []
+    input_ply = scene["model"]
+    output_ply = f"{converted_dir}/{os.path.basename(input_ply)}"
     
-    for scene in SCENES:
-        input_ply = scene["model"]
-        output_ply = f"{converted_dir}/{os.path.basename(input_ply)}"
-        
-        if not os.path.exists(output_ply):
-            print(f"\n🔄 Converting {scene['name']}...")
-            try:
-                convert_to_standard_ply(input_ply, output_ply)
-            except Exception as e:
-                print(f"❌ Error converting {input_ply}: {e}")
-                continue
-        else:
-            print(f"✅ Already converted: {output_ply}")
-        
-        # 更新場景配置
-        converted_scenes.append({
-            **scene,
-            "converted_model": output_ply
-        })
-    
-    return converted_scenes
-
-# --- 5. 選擇處理 ---
-def create_select_handler(converted_scenes):
-    """創建選擇處理函數"""
-    def on_select(evt: gr.SelectData):
-        index = evt.index
-        scene = converted_scenes[index]
-        
-        if "converted_model" not in scene or not os.path.exists(scene["converted_model"]):
+    # 檢查是否需要轉換 (Lazy Loading)
+    if not os.path.exists(output_ply):
+        print(f"\n🔄 Converting {scene['name']} on GPU Node...")
+        try:
+            convert_to_standard_ply(input_ply, output_ply)
+        except Exception as e:
             return (
                 None,
                 scene["tracking_img"],
-                f"**Error: Converted model not found for {scene['name']}**"
+                f"**Error converting {scene['name']}: {str(e)}**"
             )
-        
-        file_size = os.path.getsize(scene["converted_model"]) / (1024 * 1024)
-        
-        print(f"\n📂 Loading: {scene['name']}")
-        print(f"   File: {scene['converted_model']}")
-        print(f"   Size: {file_size:.1f} MB\n")
-        
+    else:
+        print(f"✅ Using cached model: {output_ply}")
+
+    # 檢查檔案大小
+    if os.path.exists(output_ply):
+        file_size = os.path.getsize(output_ply) / (1024 * 1024)
         return (
-            scene["converted_model"],
+            output_ply,
             scene["tracking_img"],
-            f"**{scene['name']}** ({file_size:.1f} MB) ✓"
+            f"**{scene['name']}** ({file_size:.1f} MB) ✓ Loaded"
+        )
+    else:
+        return (
+            None, 
+            scene["tracking_img"], 
+            "**Error: File not found after conversion**"
         )
-    
-    return on_select
-
-# --- 6. UI ---
-print("\n" + "="*60)
-print("🚀 RGS-SLAM Viewer - Initializing...")
-print("="*60)
-
-# 轉換模型
-converted_scenes = initialize_converted_models()
 
+# --- 5. UI ---
 print("\n" + "="*60)
-print("✅ Ready to launch!")
+print("🚀 RGS-SLAM Viewer - Initializing UI...")
 print("="*60 + "\n")
 
 with gr.Blocks(title="RGS-SLAM Demo") as demo:
@@ -177,7 +152,7 @@ with gr.Blocks(title="RGS-SLAM Demo") as demo:
     gr.Markdown("# 🚀 RGS-SLAM Gaussian Splatting Viewer")
     gr.Markdown(
         "**3D Gaussian Splatting** reconstruction results with camera trajectories. "
-        "Models are automatically converted to viewable format."
+        "Select a scene below to load the model."
     )
     
     with gr.Row():
@@ -199,7 +174,7 @@ with gr.Blocks(title="RGS-SLAM Demo") as demo:
             """)
         
         with gr.Column(scale=3):
-            status = gr.Markdown("**👈 Select a scene to begin**")
+            status = gr.Markdown("**👈 Select a scene to begin (Conversion happens on click)**")
             
             with gr.Tab("🎯 3D Reconstruction"):
                 gr.Markdown("### Point Cloud with Colors")
@@ -217,11 +192,9 @@ with gr.Blocks(title="RGS-SLAM Demo") as demo:
                     height=600
                 )
     
-    # Event binding
-    select_handler = create_select_handler(converted_scenes)
-    
+    # Event binding (直接綁定到有 @spaces.GPU 的函式)
     scene_gallery.select(
-        fn=select_handler,
+        fn=process_and_load_scene,
         outputs=[model_viewer, trajectory_img, status]
     )