Comments (3)
Is this project active anymore? Could someone please advise?
from waymo-open-dataset.
Hi @SM1991CODES ,
The V2 dataset primarily features a different data format optimized for modular reading. Once loaded, you can process the data similarly to how you would with the V1 dataset. You may try this function to convert the segmentation label range image to point cloud:
def convert_range_image_to_point_cloud_labels_v2(
range_image: v2.perception.lidar.RangeImage,
segmentation_label: v2.perception.segmentation.LiDARSegmentationRangeImage
) -> np.ndarray:
range_image_tensor = range_image.tensor
range_image_mask = range_image_tensor[..., 0] > 0
sl_tensor = segmentation_label.tensor
sl_points_tensor = tf.gather_nd(sl_tensor, tf.where(range_image_mask))
return sl_points_tensor.numpy()
This is similar to the convert_range_image_to_point_cloud_labels
function in tutorial/tutorial_3d_semseg.ipynb.
Be sure that you select the (LiDAR) range image and segmentation label that correspond with the matched laser name and frame timestamp.
from waymo-open-dataset.
Hello,
Thank you for the help - this basically works.
But. I have another problem - I am trying to use v2.merge to combine the fillowing components:
lidar_df = read(path_dataset_root, components["lidar"], context_name)
lidar_labels_df = read(path_dataset_root, components["lidar_labels"], context_name)
lidar_calibs_df = read(path_dataset_root, components["lidar_calibs"], context_name)
ego_pose_df = read(path_dataset_root, components["ego_pose"], context_name)
lidar_seg_labels_df = read(path_dataset_root, components["lidar_seg"], context_name)
lidar_calibs_df = v2.merge(lidar_df, lidar_calibs_df)
lidar_calibs_pose_df = v2.merge(lidar_calibs_df, ego_pose_df)
lidar_labels_sem_df = v2.merge(lidar_seg_labels_df, lidar_labels_df)
lidar_calibs_labels_df = v2.merge(lidar_calibs_pose_df, lidar_labels_sem_df, left_group=True, right_group=True)
I am trying to get for each frame - point cloud, object labels, ego pose, semantic labels
This does not work.
I am aware that waymo does not provide semantic labels for each frame.
Please advise how to do this correctly.
from waymo-open-dataset.
Related Issues (20)
- Waymo Open Motion Dataset HOT 2
- Motion Dataset: Discrepancy between Point Cloud and Agent Box HOT 8
- [WOSAC] 2023 V1 leaderboard == 2024 leaderboard? HOT 1
- Cannot download dataset programmatically HOT 5
- Is the interactive prediction leader board closed? HOT 2
- How is Range Image Flow Calculated?
- a new release needed HOT 2
- Bug in womd_lidar_utils.py HOT 1
- IMU data HOT 2
- Some questions about the format(tfrecord) of the data HOT 2
- Cameras Missing HOT 1
- Speed of local evaluation for sim agents HOT 1
- Waymo submission question. HOT 4
- issue about waymo challenge 2024 validation set submission HOT 4
- Invite code?
- Distorded or undistorded images - Waymo-open-dataset v2 HOT 2
- Questions about Sim-Agents metrics of ground truth HOT 1
- Build from source fails HOT 1
- Sim agent challenge V1 metric testing score HOT 2
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