fcladera
commented
8 months ago Hi Jinghang,
We are glad M3ED is useful to you! As you well discovered, dynamic objects do not appear in the depth image as this depth is obtained from the integrated PC from Faster-LIO. During the integration phase, dynamic objects may appear blurry.
@k-chaney just created a snippet to load one of the LiDAR sweeps in the data. You can find it here: https://github.com/daniilidis-group/m3ed/blob/main/lidar_loading.py
This script requires open3d, ouster-sdk, and h5py. It loads the first LiDAR sweep f['/ouster/data'][0][...] and displays a point cloud from it.
Please let us know if you have any other questions!
Dear Authors,
I have recently been exploring the application of event cameras in urban autonomous driving scenarios and was thrilled to find that your dataset perfectly aligns with my research needs. I am particularly interested in obtaining the trajectories of other dynamic objects in urban driving scenes, which I believe your dataset could facilitate.
However, I encountered a challenge while processing the "depth_gt.h5" file, specifically in the “/depth/prophesee_left” section, where the depth values of dynamic objects appear to be omitted. I attempted to derive the 3D point clouds in the LIDAR coordinate system using the Ouster LIDAR data saved in “/ouster/data” and “/ouster/metadata” topic of the “.h5” file. Unfortunately, the information about LEGACY data format(https://static.ouster.dev/sensor-docs/image_route1/image_route2/sensor_data/sensor-data.html#legacy-data-packet-format) provided on the M3ED website seems to focus on the composition of the LEGACY data package send from LIDAR, and I am struggling to interpret the 128x12609 Numpy matrix stored in “/ouster/data”.
Given these challenges, I am writing to kindly request any available code or instructions on how to calculate the 3D point clouds in the LIDAR coordinate system or the Prophesee left camera coordinate system based on “/ouster/data” and “/ouster/metadata” in the “.h5” file. Your guidance in this matter would be invaluable and greatly enhance my understanding and utilization of your dataset.
Please rest assured that any resources you provide will be used strictly for research purposes, and I will ensure that all due credit is given to your groundbreaking work. If there are any conditions or agreements necessary for the use of the code or data, I am more than willing to comply with them.
Thank you very much for considering my request. I greatly appreciate your time and assistance, and I am looking forward to potentially discussing your work further.
Best regards,