apparently can't render point clouds anyway, go right to reconstruction

app.py

@@ -11,18 +11,22 @@ import spaces
 
 
 @spaces.GPU(duration=60 * 3)
-def run_on_gpu(input_point_cloud_viewer,
+def run_on_gpu(input_point_cloud: gr.utils.NamedString,
                gen_resolution_global,
                padding_factor,
                gen_subsample_manifold_iter,
                gen_refine_iter):
     print('Started inference at {}'.format(datetime.datetime.now()))
+    print('Inputs:', input_point_cloud, gen_resolution_global, padding_factor,
+          gen_subsample_manifold_iter, gen_refine_iter)
+    print('Types:', type(input_point_cloud), type(gen_resolution_global), type(padding_factor),
+          type(gen_subsample_manifold_iter), type(gen_refine_iter))
 
     import os
     os.chdir(os.path.dirname('./ppsurf'))
 
-    in_file = 'data/{}'.format(input_point_cloud_viewer)
-    out_file = 'results/rec/{}'.format(input_point_cloud_viewer)
+    in_file = 'data/{}'.format(input_point_cloud.name)
+    out_file = 'results/rec/{}'.format(input_point_cloud.name)
 
     call_base = ['python', 'pps.py', 'rec']
     call_args = [in_file,
@@ -58,36 +62,36 @@ def main():
     Inference takes about 2 minutes.
     '''
 
-    def convert_to_ply(input_point_cloud_upload: gr.utils.NamedString):
-
-        # add absolute path to import dirs
-        import sys
-        import os
-        sys.path.append(os.path.abspath('ppsurf'))
-
-        # import os
-        # os.chdir('ppsurf')
-
-        print('Inputs:', input_point_cloud_upload, type(input_point_cloud_upload))
-        input_shape: str = input_point_cloud_upload.name
-        if not input_shape.endswith('.ply'):
-            # load file
-            from ppsurf.source.occupancy_data_module import OccupancyDataModule
-            pts_np = OccupancyDataModule.load_pts(input_shape)
-
-            # convert to ply
-            import trimesh
-            mesh = trimesh.Trimesh(vertices=pts_np[:, :3])
-            input_shape = input_shape + '.ply'
-            mesh.export(input_shape)
-
-        print('ls\n', subprocess.check_output(['ls', os.path.dirname(input_shape)]))
-
-        # show in viewer
-        print(type(input_tabs))
-        print(type(input_point_cloud_viewer))
-        input_tabs.selected = 'pc_viewer'
-        input_point_cloud_viewer.value = input_shape
+    # def convert_to_ply(input_point_cloud_upload: gr.utils.NamedString):
+    #
+    #     # add absolute path to import dirs
+    #     import sys
+    #     import os
+    #     sys.path.append(os.path.abspath('ppsurf'))
+    #
+    #     # import os
+    #     # os.chdir('ppsurf')
+    #
+    #     print('Inputs:', input_point_cloud_upload, type(input_point_cloud_upload))
+    #     input_shape: str = input_point_cloud_upload.name
+    #     if not input_shape.endswith('.ply'):
+    #         # load file
+    #         from ppsurf.source.occupancy_data_module import OccupancyDataModule
+    #         pts_np = OccupancyDataModule.load_pts(input_shape)
+    #
+    #         # convert to ply
+    #         import trimesh
+    #         mesh = trimesh.Trimesh(vertices=pts_np[:, :3])
+    #         input_shape = input_shape + '.ply'
+    #         mesh.export(input_shape)
+    #
+    #     print('ls:\n', subprocess.run(['ls', os.path.dirname(input_shape)]))
+    #
+    #     # show in viewer
+    #     print(type(input_tabs))
+    #     # print(type(input_point_cloud_viewer))
+    #     # input_tabs.selected = 'pc_viewer'
+    #     # input_point_cloud_viewer.value = input_shape
 
     if (SPACE_ID := os.getenv('SPACE_ID')) is not None:
         description += (f'\n<p>For faster inference without waiting in queue, '
@@ -100,20 +104,19 @@ def main():
         gr.Markdown(description)
         with gr.Row():
             with gr.Column():
-                with gr.Tabs() as input_tabs:
-                    with gr.TabItem(label='Input Point Cloud Upload', id='pc_upload'):
-                        input_point_cloud_upload = gr.File(
-                            show_label=False, file_count='single')
-                        input_point_cloud_upload.upload(
-                            fn=convert_to_ply,
-                            inputs=[
-                                input_point_cloud_upload,
-                            ],
-                            outputs=[
-                                # input_point_cloud_viewer,  # not available here
-                            ])
-                    with gr.TabItem(label='Input Point Cloud Viewer', id='pc_viewer'):
-                        input_point_cloud_viewer = gr.Model3D(show_label=False)
+                # with gr.Tabs() as input_tabs:
+                #     with gr.TabItem(label='Input Point Cloud Upload', id='pc_upload'):
+                input_point_cloud_upload = gr.File(show_label=False, file_count='single')
+                        # input_point_cloud_upload.upload(
+                        #     fn=convert_to_ply,
+                        #     inputs=[
+                        #         input_point_cloud_upload,
+                        #     ],
+                        #     outputs=[
+                        #         # input_point_cloud_viewer,  # not available here
+                        #     ])
+                    # with gr.TabItem(label='Input Point Cloud Viewer', id='pc_viewer'):
+                    #     input_point_cloud_viewer = gr.Model3D(show_label=False)
                 gen_resolution_global = gr.Slider(
                     label='Grid Resolution (larger for more details)',
                     minimum=17, maximum=513, value=129, step=2)
@@ -159,7 +162,7 @@ def main():
 
         run_button.click(fn=run_on_gpu,
                          inputs=[
-                             input_point_cloud_viewer,
+                             input_point_cloud_upload,
                              gen_resolution_global,
                              padding_factor,
                              gen_subsample_manifold_iter,