Update

app.py

@@ -2,64 +2,65 @@ import gradio as gr
 import os
 
 # --- Configuration ---
+# 假設你的 .splat 檔案已經放在 "assets_converted" 資料夾中
+# 建議將檔案命名為 office0.splat, office2.splat, room0.splat 以保持簡潔
 SCENES = [
     {
         "name": "Office 0", 
-        "thumb": "assets/office0.PNG",           
-        "model": "assets_converted/office0_converted.ply",
+        "thumb": "assets/office0.PNG",            
+        "model": "assets/office0.splat", # <--- 修改處：改成 .splat 檔案
         "tracking_img": "assets/office0_tracking.PNG" 
     },
     {
         "name": "Office 2",
         "thumb": "assets/office2.PNG",
-        "model": "assets_converted/office2_converted.ply",
+        "model": "assets/office2.splat", # <--- 修改處
         "tracking_img": "assets/office2_tracking.PNG"
     },
     {
         "name": "Room 0",
         "thumb": "assets/room0.PNG",
-        "model": "assets_converted/room0_converted.ply",
+        "model": "assets/room0.splat",   # <--- 修改處
         "tracking_img": "assets/room0_tracking.PNG"
     }
 ]
 
+# 建立 Gallery 用清單
 gallery_items = [(item["thumb"], item["name"]) for item in SCENES]
 
 def load_scene(evt: gr.SelectData):
+    """
+    載入選定的場景。
+    Gradio 的 Model3D 元件會根據副檔名 (.splat) 自動切換渲染模式。
+    """
     index = evt.index
     scene = SCENES[index]
     
-    # 除錯資訊：檢查檔案是否存在
+    # 檢查檔案是否存在，避免報錯讓使用者困惑
     if not os.path.exists(scene["model"]):
-        print(f"❌ File not found: {scene['model']}")
         return (
             None,
-            scene["tracking_img"],
-            f"**Error: Model file missing on server!**\nPath: `{scene['model']}`"
+            scene["tracking_img"] if os.path.exists(scene["tracking_img"]) else None,
+            f"**⚠️ Error: File not found: {scene['model']}**\n請確認 .splat 檔案已上傳至正確路徑。"
         )
     
+    # 計算檔案大小供顯示
     file_size = os.path.getsize(scene["model"]) / (1024 * 1024)
-    print(f"📂 Loading: {scene['model']} ({file_size:.2f} MB)")
     
-    # 警告：如果檔案還是太大 (>100MB)，CPU Basic 載入還是會慢
-    if file_size > 100:
-        msg = f"**{scene['name']}** ({file_size:.1f} MB)\n⚠️ File is large, please wait..."
-    else:
-        msg = f"**{scene['name']}** ({file_size:.1f} MB) ✓ Loaded"
-
     return (
         scene["model"],
         scene["tracking_img"],
-        msg
+        f"**{scene['name']}** ({file_size:.1f} MB) ✓ Loaded (.splat)"
     )
 
 # --- UI ---
 with gr.Blocks(title="RGS-SLAM Demo") as demo:
     
     gr.Markdown("# 🚀 RGS-SLAM Gaussian Splatting Viewer")
-    gr.Markdown("Using CPU-Basic. Models converted to Binary PLY.")
+    gr.Markdown("此檢視器使用 `.splat` 格式，載入速度更快且相容性更高。")
     
     with gr.Row():
+        # 左側選單
         with gr.Column(scale=1):
             gr.Markdown("### 📂 Select Scene")
             scene_gallery = gr.Gallery(
@@ -67,22 +68,27 @@ with gr.Blocks(title="RGS-SLAM Demo") as demo:
                 label="Available Scenes",
                 columns=1,
                 height=400,
-                object_fit="contain"
+                object_fit="contain",
+                allow_preview=False # 關閉點擊預覽圖片，強制觸發選擇事件
             )
         
+        # 右側顯示區
         with gr.Column(scale=3):
-            status = gr.Markdown("**👈 Select a scene to load**")
+            status = gr.Markdown("**👈 Select a scene from the left to load**")
             
             with gr.Tab("🎯 3D Reconstruction"):
+                # Model3D 支援 .splat, .ply, .glb 等格式
                 model_viewer = gr.Model3D(
-                    label="3D Model",
-                    clear_color=[0.1, 0.1, 0.1, 1.0],
-                    height=600
+                    label="3D Gaussian Splat",
+                    clear_color=[0.0, 0.0, 0.0, 1.0], # 建議 splat 使用黑色背景
+                    height=600,
+                    interactive=True
                 )
             
             with gr.Tab("📍 Camera Trajectory"):
                 trajectory_img = gr.Image(label="Camera Path", height=600)
     
+    # 事件綁定
     scene_gallery.select(
         fn=load_scene,
         outputs=[model_viewer, trajectory_img, status]

requirements.txt

@@ -1,4 +1,4 @@
-gradio>=4.0.0
+gradio>=4.16.0
 trimesh
 plotly
 numpy