fix: optimize bounded direct Gaussian export

app.py

@@ -55,7 +55,7 @@ MAX_VIEWS = int(os.getenv("SIMAM3D_MAX_VIEWS", "8"))
 MAX_INPUT_SIDE = int(os.getenv("SIMAM3D_MAX_INPUT_SIDE", "1536"))
 FUSION_VOXEL_SIZE = float(os.getenv("SIMAM3D_FUSION_VOXEL_SIZE", "0.02"))
 FUSION_MAX_POINTS = int(os.getenv("SIMAM3D_FUSION_MAX_POINTS", "150000"))
-GAUSSIAN_MAX_POINTS = int(os.getenv("SIMAM3D_GAUSSIAN_MAX_POINTS", "100000"))
+GAUSSIAN_MAX_POINTS = int(os.getenv("SIMAM3D_GAUSSIAN_MAX_POINTS", "20000"))
 DEPTH_PIPELINE = None
 DA3_MODEL = None
 PIPELINE_LOCK = threading.Lock()
@@ -427,10 +427,12 @@ def direct_da3_gaussian_ply(prediction, run_id: str) -> tuple[str, int, int] | N
     gaussians = getattr(prediction, "gaussians", None)
     if gaussians is None:
         return None
+    print("Simam3D direct Gaussian export: reading parameters", flush=True)
     means = _prediction_array(getattr(gaussians, "means", None))
     scales = _prediction_array(getattr(gaussians, "scales", None))
     rotations = _prediction_array(getattr(gaussians, "rotations", None))
     opacities = _prediction_array(getattr(gaussians, "opacities", None)).reshape(-1)
+    print(f"Simam3D direct Gaussian export: means={means.shape} scales={scales.shape}", flush=True)
     if means.ndim == 3 and means.shape[0] == 1:
         means = means[0]
     if scales.ndim == 3 and scales.shape[0] == 1:
@@ -451,14 +453,19 @@ def direct_da3_gaussian_ply(prediction, run_id: str) -> tuple[str, int, int] | N
         means, scales, rotations, opacities = means[keep], scales[keep], rotations[keep], opacities[keep]
     harmonics = getattr(gaussians, "harmonics", None)
     if harmonics is not None:
+        # Only the DC coefficient is needed for the portable PLY color field;
+        # avoid transferring the complete SH basis from GPU memory.
+        if hasattr(harmonics, "detach") and harmonics.ndim >= 3:
+            harmonics = harmonics[..., 0]
         harmonics = _prediction_array(harmonics)
         if harmonics.ndim == 4 and harmonics.shape[0] == 1:
             harmonics = harmonics[0]
+        if harmonics.ndim == 3 and harmonics.shape[0] == 1:
+            harmonics = harmonics[0]
         if keep is not None and harmonics.shape[0] == original_count:
             harmonics = harmonics[keep]
-        if harmonics.ndim == 3 and harmonics.shape[0] == len(means):
-            dc = harmonics[..., 0]
-            colors = np.clip((dc * 0.2820947918 + 0.5) * 255.0, 0, 255).astype(np.uint8)
+        if harmonics.ndim == 2 and harmonics.shape[0] == len(means):
+            colors = np.clip((harmonics * 0.2820947918 + 0.5) * 255.0, 0, 255).astype(np.uint8)
         else:
             colors = np.full((len(means), 3), 180, dtype=np.uint8)
     else: