fix output of inference

app.py

@@ -109,11 +109,11 @@ def run_model(target_dir, model) -> dict:
     predictions["depth_conf"] = torch.stack(all_depth_conf, dim=0)  # (S, H, W)
     predictions["pose_enc"] = torch.stack(all_camera_pose, dim=0)  # (S, 9)
 
-    #print("World points shape:", predictions["world_points"].shape)
-    #print("World points confidence shape:", predictions["world_points_conf"].shape)
-    #print("Depth map shape:", predictions["depth"].shape)
-    #print("Depth confidence shape:", predictions["depth_conf"].shape)
-    #print("Pose encoding shape:", predictions["pose_enc"].shape)
+    print("World points shape:", predictions["world_points"].shape)
+    print("World points confidence shape:", predictions["world_points_conf"].shape)
+    print("Depth map shape:", predictions["depth"].shape)
+    print("Depth confidence shape:", predictions["depth_conf"].shape)
+    print("Pose encoding shape:", predictions["pose_enc"].shape)
 
     # Convert pose encoding to extrinsic and intrinsic matrices
     print("Converting pose encoding to extrinsic and intrinsic matrices...")