upd

runners/inferencer.py

@@ -115,9 +115,12 @@ class Inferencer(Runner):
         retry = 0
         pred_cr_seq = [last_pred_cr]
         success = 0
+        import time
         while len(pred_cr_seq) < max_iter and retry < max_retry:
-            
+            start_time = time.time()
             output = self.pipeline(input_data)
+            end_time = time.time()
+            print(f"Time taken for inference: {end_time - start_time} seconds")
             pred_pose_9d = output["pred_pose_9d"]
             pred_pose = torch.eye(4, device=pred_pose_9d.device)
 
@@ -125,7 +128,10 @@ class Inferencer(Runner):
             pred_pose[:3,3] = pred_pose_9d[0,6:]
             
             try:
+                start_time = time.time()
                 new_target_pts, new_target_normals = RenderUtil.render_pts(pred_pose, scene_path, self.script_path, voxel_threshold=voxel_threshold, filter_degree=filter_degree, nO_to_nL_pose=O_to_L_pose)
+                end_time = time.time()
+                print(f"Time taken for rendering: {end_time - start_time} seconds")
             except Exception as e:
                 Log.warning(f"Error in scene {scene_path}, {e}")
                 print("current pose: ", pred_pose)
@@ -140,8 +146,10 @@ class Inferencer(Runner):
                 retry += 1
                 continue
             
-
+            start_time = time.time()
             pred_cr, new_added_pts_num = self.compute_coverage_rate(scanned_view_pts, new_target_pts, down_sampled_model_pts, threshold=voxel_threshold)
+            end_time = time.time()
+            print(f"Time taken for coverage rate computation: {end_time - start_time} seconds")
             print(pred_cr, last_pred_cr, " max: ", data["seq_max_coverage_rate"])
             if pred_cr >= data["seq_max_coverage_rate"] - 1e-3:
                 print("max coverage rate reached!: ", pred_cr)