[Fix] Fix waymo converter

mmdet3d/datasets/convert_utils.py

@@ -296,7 +296,7 @@ def get_kitti_style_2d_boxes(info: dict,
             repro_rec['velocity'] = -1  # no velocity in KITTI
 
             center_3d = np.array(loc).reshape([1, 3])
-            center_2d_with_depth = box_np_ops.points_cam2img(
+            center_2d_with_depth = points_cam2img(
                 center_3d, camera_intrinsic, with_depth=True)
             center_2d_with_depth = center_2d_with_depth.squeeze().tolist()
 

mmdet3d/models/roi_heads/bbox_heads/pv_rcnn_bbox_head.py

@@ -4,6 +4,8 @@
 import numpy as np
 import torch
 from mmcv.cnn import ConvModule
+from mmdet.models.task_modules.samplers import SamplingResult
+from mmdet.models.utils import multi_apply
 from mmengine.model import BaseModule
 from mmengine.structures import InstanceData
 from torch import nn as nn
@@ -14,8 +16,6 @@
 from mmdet3d.structures.bbox_3d import (LiDARInstance3DBoxes,
                                         rotation_3d_in_axis, xywhr2xyxyr)
 from mmdet3d.utils import InstanceList
-from mmdet.models.task_modules.samplers import SamplingResult
-from mmdet.models.utils import multi_apply
 
 
 @MODELS.register_module()

mmdet3d/models/roi_heads/mask_heads/foreground_segmentation_head.py

@@ -3,14 +3,14 @@
 
 import torch
 from mmcv.cnn.bricks import build_norm_layer
+from mmdet.models.utils import multi_apply
 from mmengine.model import BaseModule
 from mmengine.structures import InstanceData
 from torch import nn as nn
 
 from mmdet3d.models.builder import build_loss
 from mmdet3d.registry import MODELS
 from mmdet3d.utils import InstanceList
-from mmdet.models.utils import multi_apply
 
 
 @MODELS.register_module()

mmdet3d/models/roi_heads/pv_rcnn_roi_head.py

@@ -2,15 +2,15 @@
 from typing import List, Optional
 
 import torch
+from mmdet.models.task_modules import AssignResult
+from mmdet.models.task_modules.samplers import SamplingResult
 from torch.nn import functional as F
 
 from mmdet3d.models.roi_heads.base_3droi_head import Base3DRoIHead
 from mmdet3d.registry import MODELS
 from mmdet3d.structures import bbox3d2roi
 from mmdet3d.structures.det3d_data_sample import SampleList
 from mmdet3d.utils import InstanceList
-from mmdet.models.task_modules import AssignResult
-from mmdet.models.task_modules.samplers import SamplingResult
 
 
 @MODELS.register_module()

tools/dataset_converters/update_infos_to_v2.py

@@ -80,9 +80,6 @@ def get_empty_lidar_points():
         num_pts_feats=None,
         # (str, optional): Path of LiDAR data file.
         lidar_path=None,
-        # (list[list[float]]): Transformation matrix from lidar
-        # or depth to image with shape [4, 4].
-        lidar2img=None,
         # (list[list[float]], optional): Transformation matrix
         # from lidar to ego-vehicle
         # with shape [4, 4].
@@ -120,6 +117,9 @@ def get_empty_img_info():
         # matrix from camera to image with
         # shape [3, 3], [3, 4] or [4, 4].
         cam2img=None,
+        # (list[list[float]]): Transformation matrix from lidar
+        # or depth to image with shape [4, 4].
+        lidar2img=None,
         # (list[list[float]], optional) : Transformation
         # matrix from camera to ego-vehicle
         # with shape [4, 4].
@@ -159,7 +159,7 @@ def get_empty_standard_data_info(
 
     data_info = dict(
         # (str): Sample id of the frame.
-        sample_id=None,
+        sample_idx=None,
         # (str, optional): '000010'
         token=None,
         **get_single_image_sweep(camera_types),

tools/dataset_converters/waymo_converter.py

@@ -69,10 +69,7 @@ def __init__(self,
             '_SIDE_LEFT',
             '_SIDE_RIGHT',
         ]
-        self.lidar_list = [
-            '_FRONT', '_FRONT_RIGHT', '_FRONT_LEFT', '_SIDE_RIGHT',
-            '_SIDE_LEFT'
-        ]
+        self.lidar_list = ['TOP', 'FRONT', 'SIDE_LEFT', 'SIDE_RIGHT', 'REAR']
         self.type_list = [
             'UNKNOWN', 'VEHICLE', 'PEDESTRIAN', 'SIGN', 'CYCLIST'
         ]
@@ -135,7 +132,8 @@ def convert_one(self, file_idx):
 
             self.save_image(frame, file_idx, frame_idx)
             self.save_calib(frame, file_idx, frame_idx)
-            self.save_lidar(frame, file_idx, frame_idx)
+            if 'testing_3d_camera_only_detection' not in self.load_dir:
+                self.save_lidar(frame, file_idx, frame_idx)
             self.save_pose(frame, file_idx, frame_idx)
             self.save_timestamp(frame, file_idx, frame_idx)
 
@@ -441,7 +439,6 @@ def create_folder(self):
             dir_list1 = [
                 self.label_all_save_dir,
                 self.calib_save_dir,
-                self.point_cloud_save_dir,
                 self.pose_save_dir,
                 self.timestamp_save_dir,
             ]
@@ -451,10 +448,12 @@ def create_folder(self):
                 dir_list2.append(self.cam_sync_label_save_dir)
         else:
             dir_list1 = [
-                self.calib_save_dir, self.point_cloud_save_dir,
-                self.pose_save_dir, self.timestamp_save_dir
+                self.calib_save_dir, self.pose_save_dir,
+                self.timestamp_save_dir
             ]
             dir_list2 = [self.image_save_dir]
+        if 'testing_3d_camera_only_detection' not in self.load_dir:
+            dir_list1.append(self.point_cloud_save_dir)
         for d in dir_list1:
             mmengine.mkdir_or_exist(d)
         for d in dir_list2: