fix

app.py

@@ -134,7 +134,7 @@ with block:
     def on_depth_reconstruction_btn_click(inputs):
         print("depth reconstruction")
         image = inputs[input_image]
-        path = dpt.generate_obj_masks2(image=image, cube_size=inputs[cube_size], masks=masks) #
+        path = dpt.generate_obj_masks2(image=image, cube_size=inputs[cube_size], masks=inputs[masks]) #
         return {pcl_figure: path}
     depth_reconstruction_btn.click(on_depth_reconstruction_btn_click, components, [pcl_figure], queue=False)
 

utils.py

@@ -195,22 +195,3 @@ def PCL3(image):
     
     return fig
 
-
-def PCL(mask, depth):
-    assert mask.shape == depth.shape
-    assert type(mask) == np.ndarray
-    assert type(depth) == np.ndarray
-    rgb_mask = np.zeros((mask.shape[0], mask.shape[1], 3))
-    rgb_mask[mask] = (1.0, 0.0, 0.0)
-    depth_o3d = o3d.geometry.Image(depth)
-    image_o3d = o3d.geometry.Image(mask)
-    rgbd_image = o3d.geometry.RGBDImage.create_from_color_and_depth(image_o3d, depth_o3d, convert_rgb_to_intensity=False)
-    # Step 3: Create a PointCloud from the RGBD image
-    pcd = o3d.geometry.PointCloud.create_from_rgbd_image(rgbd_image, o3d.camera.PinholeCameraIntrinsic(o3d.camera.PinholeCameraIntrinsicParameters.PrimeSenseDefault))
-    # Step 4: Convert PointCloud data to a NumPy array
-    points = np.asarray(pcd.points)
-    colors = np.asarray(pcd.colors)
-    mask = (colors[:, 0] == 1.0)
-    points = points[mask]
-    colors = colors[mask]
-    return points, colors