dont use lower settings

app.py

@@ -11,7 +11,6 @@ import matplotlib.pyplot as plt
 import matplotlib.colors as mcolors
 from matplotlib.colorbar import ColorbarBase
 import numpy as np
-import plotly.graph_objects as go
 import spaces
 import torch
 from huggingface_hub import snapshot_download
@@ -129,13 +128,19 @@ def _create_colorbar(
     return output_path
 
 
-def _create_pointcloud_plot(
+_SH_C0 = 0.28209479177387814
+_SPLAT_POINT_SCALE = 0.0015
+
+
+def _write_property_splat_ply(
     coords: np.ndarray,
     values: np.ndarray,
-    property_name: str,
+    output_path: str,
     colormap: str = "viridis",
-) -> go.Figure:
-    """Create an interactive 3D colored point cloud plot."""
+    point_scale: float = _SPLAT_POINT_SCALE,
+) -> str:
+    """Write a property-colored point cloud as a 3D Gaussian Splatting .ply.
+    """
     coords = np.asarray(coords, dtype=np.float32)
     values = np.asarray(values, dtype=np.float32).reshape(-1)
     if coords.ndim != 2 or coords.shape[1] != 3:
@@ -145,38 +150,37 @@ def _create_pointcloud_plot(
             f"values must be (N,), got {values.shape} for coords {coords.shape}"
         )
 
-    fig = go.Figure(
-        data=[
-            go.Scatter3d(
-                x=coords[:, 0],
-                y=coords[:, 1],
-                z=coords[:, 2],
-                mode="markers",
-                marker={
-                    "size": 2,
-                    "color": values,
-                    "colorscale": colormap,
-                    "showscale": False,
-                    "opacity": 0.9,
-                },
-            )
-        ]
-    )
-    fig.update_layout(
-        title=f"{PROPERTY_DISPLAY_NAMES.get(property_name, property_name)} Point Cloud",
-        margin=dict(l=0, r=0, t=35, b=0),
-        scene=dict(
-            xaxis=dict(visible=False),
-            yaxis=dict(visible=False),
-            zaxis=dict(visible=False),
-            aspectmode="data",
-            bgcolor="rgb(20,20,20)",
-        ),
-        paper_bgcolor="rgb(20,20,20)",
-        plot_bgcolor="rgb(20,20,20)",
-        showlegend=False,
+    vmin, vmax = float(values.min()), float(values.max())
+    if vmax - vmin > 1e-12:
+        norm = (values - vmin) / (vmax - vmin)
+    else:
+        norm = np.zeros_like(values)
+    rgb = plt.cm.get_cmap(colormap)(norm)[:, :3].astype(np.float32)  # 0..1
+
+    n = coords.shape[0]
+    fields = [
+        "x", "y", "z", "nx", "ny", "nz",
+        "f_dc_0", "f_dc_1", "f_dc_2",
+        "opacity", "scale_0", "scale_1", "scale_2",
+        "rot_0", "rot_1", "rot_2", "rot_3",
+    ]
+    arr = np.zeros((n, len(fields)), dtype=np.float32)
+    arr[:, 0:3] = coords
+    arr[:, 6:9] = (rgb - 0.5) / _SH_C0
+    arr[:, 9] = 6.0
+    arr[:, 10:13] = np.log(point_scale)
+    arr[:, 13] = 1.0
+
+    header = (
+        "ply\nformat binary_little_endian 1.0\n"
+        f"element vertex {n}\n"
+        + "".join(f"property float {f}\n" for f in fields)
+        + "end_header\n"
     )
-    return fig
+    with open(output_path, "wb") as fp:
+        fp.write(header.encode("ascii"))
+        fp.write(arr.tobytes())
+    return output_path
 
 
 def _create_material_visualizations(
@@ -225,11 +229,12 @@ def _create_material_visualizations(
 
     for prop_name, prop_data in properties.items():
         if prop_data is not None:
-            plot = _create_pointcloud_plot(coords_normalized, prop_data, prop_name)
+            ply_path = os.path.join(output_dir, f"{prop_name}_cloud.ply")
+            _write_property_splat_ply(coords_normalized, prop_data, ply_path)
             colorbar_path = os.path.join(output_dir, f"{prop_name}_colorbar.png")
             _create_colorbar(prop_data, prop_name, colorbar_path)
-            result[prop_name] = (plot, colorbar_path)
-            print(f"Created point cloud plot for {prop_name}")
+            result[prop_name] = (ply_path, colorbar_path)
+            print(f"Created point cloud for {prop_name}")
 
     return result
 
@@ -258,9 +263,8 @@ def process_3d_model(input_file):
             print(f"Processing as Gaussian splat: {input_file}")
             results = model.get_splat_materials(
                 input_file,
-                voxel_method="kaolin",
-                query_points="voxel_centers",
                 output_dir=output_dir,
+                seed=42,
             )
         else:
             print(f"Processing as mesh: {input_file}")
@@ -385,7 +389,7 @@ Upload a Gaussian Splat (.ply) to predict volumetric mechanical properties (Youn
 """
 
 
-with gr.Blocks(css=css, title="VoMP") as demo:
+with gr.Blocks(title="VoMP") as demo:
     gr.HTML(title_md)
     gr.Markdown(description_md)
 
@@ -408,17 +412,29 @@ with gr.Blocks(css=css, title="VoMP") as demo:
                 # Row 1: Young's Modulus and Poisson's Ratio
                 with gr.Row():
                     with gr.Column(scale=1, min_width=200):
-                        youngs_cloud = gr.Plot()
+                        youngs_cloud = gr.Model3D(
+                            label="Young's Modulus",
+                            clear_color=[0.1, 0.1, 0.1, 1.0],
+                            height=400,
+                        )
                         youngs_colorbar = gr.Image(height=50, show_label=False)
 
                     with gr.Column(scale=1, min_width=200):
-                        poissons_cloud = gr.Plot()
+                        poissons_cloud = gr.Model3D(
+                            label="Poisson's Ratio",
+                            clear_color=[0.1, 0.1, 0.1, 1.0],
+                            height=400,
+                        )
                         poissons_colorbar = gr.Image(height=50, show_label=False)
 
                 # Row 2: Density and Download
                 with gr.Row():
                     with gr.Column(scale=1, min_width=200):
-                        density_cloud = gr.Plot()
+                        density_cloud = gr.Model3D(
+                            label="Density",
+                            clear_color=[0.1, 0.1, 0.1, 1.0],
+                            height=400,
+                        )
                         density_colorbar = gr.Image(height=50, show_label=False)
 
                     with gr.Column(scale=1, min_width=200):
@@ -465,4 +481,4 @@ with gr.Blocks(css=css, title="VoMP") as demo:
     )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(css=css)